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How does bacteriorhodopsin differ from the rhodopsin present in mammalian eyes?

How does bacteriorhodopsin differ from the rhodopsin present in mammalian eyes?


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In my high school textbook, it is written that they are similar. So, I was just curious to know about this. Thank you.


Although they are similar in both bacteriorhodopsins and rhodopsins being retinal-binding proteins, the similarity in their amino acid sequence is very limited.

The key difference between them is that rhodopsin is a G-protein-coupled receptor, and this is not the case with bacteriorhodopsin. A quick Google search on Bacteriorhodopsin vs Rhodopsin will send you to a Wikipedia article that says:

Bacteriorhodopsin belongs to the microbial rhodopsins. They have similarities to vertebrate rhodopsins, the pigments that sense light in the retina. Rhodopsins also contain retinal; however, the functions of rhodopsin and bacteriorhodopsin are different, and there is limited similarity in their amino acid sequences. Both rhodopsin and bacteriorhodopsin belong to the 7TM receptor family of proteins, but rhodopsin is a G protein-coupled receptor and bacteriorhodopsin is not.

A very good paper if you would like to know more about the two is by H. Gobind Khorana on the Two light-transducing membrane proteins.


The evolutionary relationship between microbial rhodopsins and metazoan rhodopsins.

Rhodopsin is a class of proteins whose common features are a seven-transmembrane alpha-helix apoprotein and a cofactor of retinal [1, 2]. Retinal works as a rhodopsin's chromophore which is responsible for light absorption. It reversibly and covalently binds to a lysine in the seventh helix of apoprotein. So to speak, the protein part of rhodopsin is its structural foundation while the retinal is rhodopsin's functional backbone. Rhodopsins are ubiquitously found in three domains of life--archaea, eubacteria, and eukaryotes [3-7]. According to their protein sequences, rhodopsins can be classified into two groups--Type 1 rhodopsins and Type 2 rhodopsins [2]. Type 1 rhodopsins exist in single-celled organisms while Type 2 rhodopsins only appear in multicellular animals. For convenience, we call Type 1 rhodopsins microbial rhodopsins and Type 2 rhodopsins metazoan rhodopsins in this study. Microbial rhodopsins function as phototaxis receptors (sensory rhodopsin), light-driven proton or chloride ion transporters (bacteriorhodopsin and halorhodopsin) [2, 3, 5, 6, 8]. Metazoan rhodopsins mainly function as visual receptors in animal's eyes such as rod or cone opsins [9-11]. Like microbial rhodopsins, metazoan rhodopsins also perform nonsensory functions. Melanopsin, expressed in brain and eyes, may be involved in circadian rhythms and papillary reflex [12]. Neuropsin (Opn5) is expressed in predominantly neural tissues [13]. Encephalopsin is expressed in brain and visceral organs [14]. RGR opsin, expressed in the retinal pigment epithelium (RPE) and Muller cells, functions as the photoisomerase [15, 16]. Peropsin is expressed in the retinal pigment epithelium (RPE) cells [17]. So far researchers have identified nine subgroups of nonvisual opsins in Metazoa [1821].

The evolutionary relationship between microbial rhodopsins and metazoan rhodopsins is difficult to decide, because they show no clearly detectable identity at sequence level. Although lacking in sequence identity cannot be used to prove that they are not homologous proteins, sequence identity is the cornerstone for conventional knowledge of protein homology [22]. Due to evolutionary divergence, the sequence identity in different homologous proteins decreases with time. Our ability to detect sequence homology in related proteins depends on their divergence rate and evolutionary distance [23]. Using PAM matrix, Dayhoff et al. show that the limitation of sequence identity for deducing protein homology is around 20% identity [23]. If two proteins share less than 20% sequence identity, it means either they are not homologous proteins or their common origin is obliterated in evolution.

There are two possible evolutionary scenarios for microbial rhodopsins and metazoan rhodopsins: (1) using retinal as chromophore, binding retinal with a lysine and similar seven-transmembrane domain are the result of convergent evolution (2) their common features are the legacy of a common ancestor, yet their sequence identity is hardly detectable because of the quick and/or longtime divergence.

To investigate the evolutionary relationship between microbial rhodopsins and metazoan rhodopsins, we have to bypass the problem of lacking sequence similarity. Fitch developed a statistical method to distinguish homologous proteins from nonhomologous ones [24]. His method compares the ancestral state from one protein group with the ancestral state from another. It circumvents the need of sequence identity to decide the evolutionary relationship between two groups of proteins. In this study, we used his method to test whether microbial rhodopsins and metazoan rhodopsins are homologous proteins or not.

2.1. Structure Data. A direct search in PDB database came back with two metazoan rhodospins and five microbial rhodopsins with structure data (Table 1).

2.2. Sequence Data. The whole genome protein sequences and corresponding cDNA sequences for twenty-seven metazoan species were downloaded from Ensembl database, NCBI database, and VectorBase [25]. These species cover seven phyla--Porifera, Cnidaria, Nematoda, Arthropoda, Chordata, Hemichordata, and Echinodermata. The species in Chordata also represented major classes in this phylum. We used a Perl script to extract the longest transcripts for each genome in this study.

2.3. BLAST and FASTA Search for Rhodopsin Genes in Genome Data. We used BLAST to search for rhodopsin genes in microbial genomes [26]. Using five microbial rhodopsins with structure data as queries, we searched the complete microbe genome database, fungi genome database, and green algae genome database on NCBI website. The BLAST parameters were set as follows: max target sequences were 500, expect threshold was 0.001, and the others were default.

We used FASTA 3.5 to search for rhodopsin genes in each metazoan genome [27]. Two metazoan rhodopsins with structure data served as queries. The E-value for FASTA search was set as 0.001.

Hits in BLAST or FASTA search result were aligned back to query sequences using MUSCLE with default parameters [28]. The hits were identified as candidate rhodopsins only when they share a conserved retinal-binding lysine in the seventh helix as the same position as queries. We removed redundant candidate hits and any sequence shorter than 200 amino acids or longer than 1000 amino acids.

2.4. Structure Alignment. Using their PBD files, two metazoan rhodospin protein structures and five microbial rhodopsin protein structures were aligned with CE-MC multiple protein structure alignment server with default parameters [29].

2.5. Sequence Alignment. Microbial or metazoan rhodopsin protein sequences were aligned using MUSCLE with default parameters [28]. All nucleotide sequences in this study were aligned according to their protein sequence alignment result.

2.6. Test Region Selection. Although there is no clearly detectable sequence identity, protein structure is something comparable between microbial and metazoan rhodopsins. The selection of test region between microbial and metazoan rhodopsins was based on their structure alignment. The problem we encountered here is that structure data are far scarcer than sequence data in both groups of rhodopsins. Only two metazoan rhodospins and five microbial rhodopsins have structure data. So we have to use their structure alignment as a guide to infer seven-transmembrane domain in their sequence alignment.

All microbial rhodopsins share a clearly detectable sequence homology as well as all metazoan rhodopsins, so sequence alignment result is reliable within microbial or metazoan group. However, structure alignment result does not always coincide with sequence alignment result that is, the positional homology proposed by microbial structure alignment may not be the same one proposed by microbial sequence alignment. Our solution is that we first aligned all microbial rhodospin sequences using MUSCLE. Then we picked out five microbial rhodopsin sequences with structure data in MUSCLE alignment result and compared their sequence alignment with their structure alignment. By doing so, we could identify the positional homology agreed by both alignment methods. We repeated this practice in metazoan rhodopsins using squid and bovine rhodopsins' structure alignment as a guide. The final test region is the alignment result agreed by both structure and sequence alignments.

2.7. Phylogenetic Analysis and Ancestral State Inference. Neighbor-joining, Bayesian, and maximum-likelihood methods were used to construct phylogenetic tree for microbial or metazoan rhodopsins. ProtTest was used to select evolution models for our phylogenetic analyses [30]. MEGA 5 was used to construct NJ tree with "pairwise deletion" option and "JTT" model [31]. Rates and patterns were set as "Gamma Distributed", and Gamma parameter was set as "4". Bootstrap method was used to test phylogeny, and number of bootstrap replications was set as "500". PhyML 3.0 was used to construct ML tree with "WAG" model [32]. Proportion of invariable sites and gamma shape parameter were estimated from alignment result. Approximate likelihood-ratio test was used to test for branch reliability [33]. MrBayes 3.1.1 was used to construct Bayesian tree with "WAG" model [34]. We ran for 500, 000 generations and sampled posterior probability trees every 1000 generations. We summarized 25% of both parameter values and trees to get the consensus tree.

PHYLIP package was used to construct Fitch-Margoliash tree for rhodopsin genes within each metazoan species [35]. Within-species rhodopsin tree was built with "JTT" model and tested with 100 bootstrap replicates.

Phylogenetic trees served as the evolutionary history for our ancestral state inference. Parsimony method was used to infer ancestral states [24]. We wrote a Perl script to implement this method.

2.8. Test for Relatedness in Ancestral States. The test for relatedness in two ancestral states is a statistic method Fitch devised in his 1970 paper [24]. The basic idea behind this test is that the probability of relatedness can be calculated by comparing the observed mutation distance between two ancestral states with the expected mutation distance between them. The observed mutation distance is the actual nucleotide differences between two ancestral states. The expected mutation distance between two ancestral states is the probability of randomly chosen disjoint nucleotide sets between them multiplied by the length of their sequence. The standard deviation between two distances is the square root of expected distance multiplied by the probability of randomly chosen intersectant nucleotide sets between them. The number of standard deviations between the observed mutation distance and the expected mutation distance follows normal distribution. The probability of its value could be found in the table of normal probability and it is used as the probability of significance.

3.1. Structural Homology between Microbial Rhodopsin and Metazoan Rhodopsin. The structure alignment of five microbial rhodopsins and two metazoan rhodospins shows that all rhodopsins share a remarkable structural homology (Figure 1). Seven-transmembrane helices are conserved within microbial or metazoan rhodopsins and between them.

Although there is no clearly detectable sequence homology between these two groups of rhodopsins, the structure alignment reveals that they share a conserved WXXY sequence motif in the sixth helix. Interestingly, the lysine that binds retinal in the seventh is not structurally conserved and locates in different position between them. There is also an/a insertion/deletion in the seventh helix between these two groups of rhodopsins, which is just one amino acid before the crucial lysine in microbial rhodopsins (insertion) or one amino acid after the crucial lysine in metazoan rhodopsins (deletion). So the position of retinal-binding lysine shifts three amino acids forward in metazoan rhodopsins.

3.2. Rhodopsin Genes in Microbial and Metazoan Genomes. BLAST search for microbial rhodopsins came back with 62 microbial rhodopsins (See Table S1 in Supplementary Material available online at http://dx.doi.org/10.1155/2013/435651). FASTA search for metazoan rhodopsins came back with 227 metazoan rhodopsins from 25 species (Table 2).

In 62 microbial rhodopsins, thirty-five of them are from bacteria, twenty-four are from archaea, and three are from eukaryotes. Bacterium Salinibacter ruber M8 and archaea Haloarcula marismortui ATCC 43049 have four different copies of rhodopsin gene. One bacterium species and four archaea species have three different rhodopsin genes. Eleven microbial species have two different rhodopsin genes. Among three eukaryotic microbial rhodopsins, two of them are from single-celled green alga Chlamydomonas reinhardtii and one is from encapsulated yeast Cryptococcus neoformans var. neoformans.

Table 2 shows the number of rhodopsin genes in each metazoan species. We named rhodospin genes in numeric order within each metazoan species. The number of rhodopsin genes varies drastically in each metazoan species. In insects, malaria mosquito has nine rhodopsin genes while body blouse only has three. There is no rhodopsin gene found in sponge Amphimedon queenslandica and nematode Caenorhabditis elegans, although they do have rhodopsin-related genes.

3.3. Final Test Region. The final test region we selected is the consistent alignment result between structure and sequence alignments. There is no consistent region found in helices A, B, or D. In helix C, there is an 18-amino acid consistent region. In helix E, there are two consistent regions: one is 11 amino acid long and the other is 14 amino acid long. In helix F, there is a 25-amino acid consistent region. In helix G, there is an 18-amino acid consistent region. The total test region is 86 amino acid long and equals 258 nucleotides.

3.4. The Evolutionary History and Ancestral State Inference in Metazoan Rhodopsins. We used three different methods to construct phylogenetic trees for all metazoan rhodopsins in this study. Hydra rhodopsins serve as an outgroup to root metazoan trees. In our study, Hydra is the only animal from Cnidaria. It is the basal phylum to Arthropoda, Chordata, Hemichordata, and Echinodermata. Rooted with Hydra rhodopsins, three trees show three different overall topologies. Neighbor-joining tree shows all rhodopsin genes divided into three major clades except Hydra rhodopsins (Supplemental Figure 1). One clade mainly consists of chordate rhodopsins and no arthropod rhodopsins. The other two clades contain both chordate and arthropod rhodopsins. Maximum-likelihood tree shows a different evolutionary history from NJ tree (Supplemental Figure 2). ML tree has four major clades instead of three. Bayesian tree shows a more complicated evolutionary history (Supplemental Figure 3). Three separate clades in NJ tree are mixed in Bayesian tree. We did not know which tree is the most reliable one in all three trees. Three trees produced three different ancestral states. Only one state is true, because all metazoan rhodopsins share only one evolutionary history.

In order to get reliable ancestral state, we constructed the phylogenetic tree for rhodopsins within each metazoan species instead of for all metazoan rhodopsins (Figures 2(a) and 2(b)). By reducing the number of taxa in tree construction, we could get more reliable trees for ancestral state inference. Nevertheless, by doing so, we had to infer one ancestral state for each metazoan species. Using one Hydra rhodopsin as an outgroup, we constructed 24 metazoan rhodopsin trees and inferred 24 ancestral states based on these trees. Eighteen of them are possible metazoan rhodopsin's ancestral states in Chordata. Four of them are possible ancestral states in Arthropoda. Two of them are possible ancestral states in Hemichordata and Echinodermata.

3.5. The Evolutionary History and Ancestral State Inference in Microbial Rhodopsins. We also used three different methods to construct phylogenetic trees for all microbial rhodopsins. Three microbial trees are consistent in overall topologies, although they differ in the position of one branch which contains six bacteria rhodopsins (Supplemental Figures 4, 5, and 6). The problem is that bacteria and archaea are sister clades in biological systematics. It means that we are unable to root microbial trees. If we could not decide an outgroup for microbial trees, we would not be capable of inferring any ancestral state with them.

To overcome this problem, we first tried to find which microbial subtree is the most possible candidate tree for ancestral state inference. Using Fitch's method, we tested each extant microbial rhodospin gene with 24 metazoan ancestral states. We found that three microbial rhodopsins are distantly related to metazoan ancestral states with statistical significance (Supplemental Table 2). These three rhodopsins are all located in one single subtree which contains 13 microbial rhodopsins (Figure 3). Thenweinferred all possible microbial rhodopsin's ancestral states on this subtree.

3.6. The Relatedness between Microbial Rhodopsins' Ancestral States and Metazoan Rhodopsins' Ancestral States. We tested 24 metazoan rhodopsin's ancestral states with all possible microbial rhodopsin's ancestral states on the candidate subtree. Among all inferred microbial rhodopsin's ancestral states, one microbial rhodopsin's ancestral state has the smallest mutation distance with metazoan rhodopsin's ancestral states (Figure 3). This microbial ancestral state is reconstructed upon one fungi rhodopsin, one bacteria rhodopsin, and eight archaea rhodopsins. Test result shows that 13 metazoan rhodopsin's ancestral states are divergently related to it with statistical significance (Table 3). These ancestral states cover Arthropoda, Chordata, Hemichordata, Echinodermata, and two subphyla in Chordata--Tunicata (sea squirt) and Cephalochordata (amphioxus).

4.1. Structural Homology versus Common Origin. Microbial rhodopsins and metazoan rhodopsins share a remarkable structural homology in their seven helices (Figure 1). However, the structural homology does not necessarily indicate the common origin. The empirical view of common origin is based on sequence homology. Convergent evolution is also a probable cause for structural homology [36]. Through both structure alignment and sequence alignment, we found that the vast majority of microbial and metazoan rhodopsins share a conserved WXXY sequence motif in the sixth helix. The tryptophan and tyrosine in this motif are crucial amino acids which form retinal-binding pocket in both groups of rhodopsins [37-41]. The conservation of WXXY motif in both groups of rhodopsin can be explained by either convergent evolution or common origin. In this case, common origin seems to be more plausible than convergent evolution. According to PAM matrix, tryptophan is the least mutable amino acid and tyrosine is the fifth-least mutable amino acid [23].

4.2. The Convoluted Evolutionary History of Metazoan Rhodopsins. There is only one rhodopsin gene found in acorn worm while there are 35 rhodopsin genes found in zebra fish. No rhodopsin gene found in sponge and nematode indicates that rhodopsin is not essential for the survival of metazoa. However, photoreception capability does grant animals a great advantage for their survival. Nonessentiality and advantage for survival render the evolution of metazoans rhodopsins a birth-and-death process, in which gene duplication event creates new genes and some newly-created genes are kept in genome while others vanish from genome by accumulating deleterious mutations [42]. This process led to the various number of rhodopsin genes in different metazoan species for example, body louse has three different rhodopsin genes while malaria mosquito has nine, and both of them are insects. It also made divergence and subfunctionalization rampant among duplicated rhodopsin genes. There are at least ten different subgroups of metazoan rhodopsins, and only one subgroup directly functions as visual opsins [11, 1821]. The birth-and-death process produced a very complicated evolutionary history for metazoan rhodopsins. Due to their convoluted evolutionary history and the large number of sequences used in phylogenetic analysis, we could not acquire an accurate phylogenetic tree for all metazoan rhodopsins. So in ancestral state inference, we used each species' rhodopsin genes to perform phylogenetic analysis in order to build a reliable tree within each metazoan species.

4.3. Gene Duplication and Horizontal Gene Transfer in Microbial Rhodopsins. Gene duplication and horizontal gene transfer are common in microbial rhodopsins. Two microbial species have four rhodopsin genes, five species have three rhodopsin genes, and eleven species have two rhodopsin genes (Supplemental Table 1). Both of the gene duplication and horizontal gene transfers contribute to multiple rhodopsin copies in these species. For example, bacterium Salinibacter ruber M8 has four rhodopsin genes. Its two sensory rhodopsins (Bac_Sal_s1 and Bac_Sal_s2) were the result of a gene duplication event, but they are clustered with archaea rhodopsins in microbial tree. It means that Salinibacter ruber M8 got its original sensory rhodopsin from archaea through horizontal gene transfer. Horizontal gene transfer makes the origin of microbial rhodopsins untraceable. The fact that all three domains of life have microbial rhodopsins proposes that microbial rhodopsin is a very ancient gene. It could be as old as life itself.

4.4. Are Metazoan Rhodopsins and Microbial Rhodopsins Homologous Genes? The main purpose of this study is to answer the question: are metazoan rhodopsins and microbial rhodopsins homologous genes? Due to the lack of direct evidence--sequence homology, we tried to answer this question by comparing their ancestral states. The complicated evolutionary history of metazoan rhodopsins made a reliable overall phylogenetic tree hardly possible. We circumvented this problem by building the phylogenetic tree for metazoan rhodopsins within each species. Then using these reliable trees, we inferred one ancestral state for each metazoan species.

In our 24 metazoan rhodopsin's ancestral states, more than half of them are divergently related to the microbial rhodopsin's ancestral state with statistical significance and less than half of them without statistical significance (Table 2). There are two possible explanations for the reason why the other 11 metazoan rhodopsin's ancestral states show no statistical significance: (1) the birth-and-death process eliminated some basal metazoan rhodopsins in these species. Therefore, their phylogenetic trees only allowed us to trace back to a recent ancestral state instead of a much more ancient one (2) in these species, the existent metazoan rhodopsins diverge from their ancestor so greatly that there is no traceable information left in their sequences. These two explanations are not mutually exclusive.

For thirteen metazoan rhodopsin's ancestral states divergently related to the microbial rhodopsin's ancestral states with statistical significance, does it mean that metazoan rhodopsin and microbial rhodopsin are homologous genes? By the definition of Fitch's test, the answer is yes. The test region we selected is total 86 amino acids. Within test region, the average mutation distance between existent metazoan and microbial rhodopsin is 119 [+ or -] 5 mutations in the first and second codon positions. Assuming one mutation in the first or second codon position would change its coding amino acid, each paired codon in the test region averagely shares about 1.38 mutations between two rhodopsin groups. It explains why we cannot find clearly detectable sequence homology between microbial and metazoan rhodopsins. After ancestral state reconstruction, the shortest mutation distance between microbial and metazoan ancestral states was 63 mutations. It is found between chicken and one microbial ancestral state inferred on nine microbial rhodopsins, with a P value of 0.0045. There are total 86 amino acids in the test region. If mutations were evenly distributed in each codon, there would be 63 amino acid differences between microbial and metazoan ancestral states. In another words, the sequence identity between microbial and metazoan ancestral states would be 23 amino acids. 23 divided by 86, it is about 26.7% sequence identity.

In pairwise sequence alignment, over 30% sequence identity is the safe standard for homologous proteins. Proteins sharing from 15% to 30% sequence identity are in the twilight zone, which means their homologous status is still in ambiguity [22]. Even when tracing back in time by reconstructing ancestral states, our result shows that only 26.7% sequence identity might exist in four helices between ancestral microbial and metazoan rhodopsins. In conventional viewpoint, such result still cannot prove that metazoan and microbial rhodopsins are homologous proteins. Using Hydra rhodopsin as an outgroup, we can only infer metazoan ancestral rhodopsin states as early as in bilaterian ancestors. Fossil records show that the earliest bilaterian animal appeared about 580 million years ago [43]. However, based on the estimation of nuclear genes, early metazoan divergence can be traced back to 830 million years ago [44]. There is no rhodopsin gene found in sponge, and the closest microbe species related to Metazoa in this study is fungus Cryptococcus neoformans var. neoformans. So we have at least 250-million-year divergence time between microbial and metazoan ancestral states. Such longtime divergence could explain the low sequence identity between microbial and metazoan ancestral states. Certainly, the low sequence identity could also be seemingly explained by convergent evolution, which means rhodopsin gene appeared independently in microbes and Metazoa. But our result shows that ancestral microbial rhodopsins and ancestral metazoan rhodopsins shared about 26.7% sequence identity in four helices. It is implausible to believe that random mutations would create an almost identical structure by generating long strings of amino acids with similar sequences.

4.5. The Position of Retinal-Binding Lysine in the Seventh Helix. The structure alignment of microbial and metazoan rhodopsins shows an intriguing phenomenon: although both groups of rhodopsins have a retinal-binding lysine in the seventh helix, the position of this lysine is not structurally conserved between them (Figure 1). Its position shifts three amino acids forward in metazoan rhodopsins. Once again the different position of retinal-binding lysine could be simply explained by convergent evolution. However, most microbial rhodopsins have an aspartic acid in the position where metazoan rhodopsins have a retinal-binding lysine. In microbial rhodopsins, this aspartic acid functions as a part of counterion which balances the positive charge of retinal-binding lysine [45, 46]. Since structure alignment and ancestral state tests suggest that microbial and metazoan rhodopsins are homologous proteins, it means that this negatively charged aspartic acid in microbial rhodopsin mutated to the positively charged retinal-binding lysine in metazoan rhodopsin. The genetic code for aspartic acid is GAC or GAT while the genetic code for lysine is AAG or AAA. These two amino acids share the same adenine at the second codon position. The second codon position tends to have the slowest mutation rate among three codon positions [47]. It is probable that Asp (GAC or GAT coding) first mutated to Asn (AAC or AAT coding) and then Asn mutated to Lys (AAG or AAA coding) during the evolution of rhodopsin gene.

The retinal-binding lysine in the seventh helix is the most crucial amino acid for rhodospin's photoreception function. It binds the chromophore retinal which is responsible for light absorption [1, 2]. If microbial and metazoan rhodopsins are homologous proteins, their retinal-binding lysine at different positions means that the function of photoreception was once lost during the evolution of rhodopsin gene. In metazoan rhodopsin, rescue mutation of this lysine salvaged the function of photoreception in metazoan rhodopsin. The once-lost lysine explains why there is no clearly detectable sequence homology between microbial and metazoan rhodopsins. During the evolution from single-celled organisms to multicellular animals, the rhodopsin gene in early metazoan ancestor lost retinal-binding lysine and therefore lost its function of photoreception. Loss of function freed the rhodopsin gene from functional constraint, and the process of divergence quickly changed its original sequence beyond recognition. Inexplicably in the later metazoan evolution, one of those loss-function rhodopsin genes managed to retrieve a lysine in its seventh helix through random mutation and therefore rescued its function of photoreception.

Based on our analysis, we propose that microbial and metazoan rhodopsins are homologous proteins and the function of photoreception was once lost during the evolution of rhodopsin gene. This conclusion maybe controversial under the conventional view for homologous proteins. Logically, the view that microbial and metazoan rhodopsins are homologous proteins is the most parsimonious one. It does not require another protein to be the precursor of metazoan rhodopsins. Nature just recycled seven-transmembrane-helix protein for photoreception. However, the alternative view that the nearly identical structure between microbial and metazoan rhodopsins is the result of convergent evolution requires random mutations to create seven-transmembranehelix domain twice through generating long strings of amino acids with similar sequences. Seven-transmembrane-helix domain does perform other functions than photoreception in Metazoa [48]. They form a large protein family of G-proteincoupled receptors which include metazoan rhodopsin and olfactory receptor. Research shows that most of these seven-transmembrane receptors share a common origin [49]. It is natural for someone to wonder what was the origin of all these seven-transmembrane receptors. There is no ancient seven-transmembrane receptor other than microbial rhodopsins which could be as old as life itself. For those who believe that the identical structure between microbial and metazoan rhodopsins is a result of convergent evolution, they will have to answer such two questions: (1) what was the precursor for all seven-transmembrane receptors in Metazoa (2) if such a precursor existed, how could random mutations shape it into seven-transmembrane helices through generating long strings of amino acids which are also similar to a subset of microbial rhodopsins? On the other hand, our ancestral state inference failed to provide a decisive sequence identity between microbial and metazoan ancestral rhodopsins. The ambiguous sequence identity could be explained by once-relieved functional constraint and the long divergence time between microbes and metazoa. The divergence-time gap might be filled by using rhodopsin-related genes from basal animals for ancestral state inference. The future genome projects for basal animals could hold the ultimate answer to the question of the evolutionary relationship between microbial rhodopsin and metazoan rhodopsin.

The authors thank Dr. Xun Gu (Fudan University and Iowa State University) for his research suggestions in this research. This research was supported by grants from the National Basic Research Program (2012CB944600), Ministry of Science and Technology (2011BAI09B00), and National Science Foundation of China (30890034).

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Libing Shen, Chao Chen, Hongxiang Zheng, and Li Jin

State Key Laboratory of Genetic Engineering and Key Laboratory of Contemporary Anthropology of Ministry of Education, School of Life Sciences, Fudan University, Shanghai 200433, China


The Evolutionary Relationship between Microbial Rhodopsins and Metazoan Rhodopsins

Rhodopsins are photoreceptive proteins with seven-transmembrane alpha-helices and a covalently bound retinal. Based on their protein sequences, rhodopsins can be classified into microbial rhodopsins and metazoan rhodopsins. Because there is no clearly detectable sequence identity between these two groups, their evolutionary relationship was difficult to decide. Through ancestral state inference, we found that microbial rhodopsins and metazoan rhodopsins are divergently related in their seven-transmembrane domains. Our result proposes that they are homologous proteins and metazoan rhodopsins originated from microbial rhodopsins. Structure alignment shows that microbial rhodopsins and metazoan rhodopsins share a remarkable structural homology while the position of retinal-binding lysine is different between them. It suggests that the function of photoreception was once lost during the evolution of rhodopsin genes. This result explains why there is no clearly detectable sequence similarity between the two rhodopsin groups: after losing the photoreception function, rhodopsin gene was freed from the functional constraint and the process of divergence could quickly change its original sequence beyond recognition.

1. Introduction

Rhodopsin is a class of proteins whose common features are a seven-transmembrane alpha-helix apoprotein and a cofactor of retinal [1, 2]. Retinal works as a rhodopsin’s chromophore which is responsible for light absorption. It reversibly and covalently binds to a lysine in the seventh helix of apoprotein. So to speak, the protein part of rhodopsin is its structural foundation while the retinal is rhodopsin’s functional backbone. Rhodopsins are ubiquitously found in three domains of life—archaea, eubacteria, and eukaryotes [3–7]. According to their protein sequences, rhodopsins can be classified into two groups—Type 1 rhodopsins and Type 2 rhodopsins [2]. Type 1 rhodopsins exist in single-celled organisms while Type 2 rhodopsins only appear in multicellular animals. For convenience, we call Type 1 rhodopsins microbial rhodopsins and Type 2 rhodopsins metazoan rhodopsins in this study. Microbial rhodopsins function as phototaxis receptors (sensory rhodopsin), light-driven proton or chloride ion transporters (bacteriorhodopsin and halorhodopsin) [2, 3, 5, 6, 8]. Metazoan rhodopsins mainly function as visual receptors in animal’s eyes such as rod or cone opsins [9–11]. Like microbial rhodopsins, metazoan rhodopsins also perform nonsensory functions. Melanopsin, expressed in brain and eyes, may be involved in circadian rhythms and papillary reflex [12]. Neuropsin (Opn5) is expressed in predominantly neural tissues [13]. Encephalopsin is expressed in brain and visceral organs [14]. RGR opsin, expressed in the retinal pigment epithelium (RPE) and Müller cells, functions as the photoisomerase [15, 16]. Peropsin is expressed in the retinal pigment epithelium (RPE) cells [17]. So far researchers have identified nine subgroups of nonvisual opsins in Metazoa [18–21].

The evolutionary relationship between microbial rhodopsins and metazoan rhodopsins is difficult to decide, because they show no clearly detectable identity at sequence level. Although lacking in sequence identity cannot be used to prove that they are not homologous proteins, sequence identity is the cornerstone for conventional knowledge of protein homology [22]. Due to evolutionary divergence, the sequence identity in different homologous proteins decreases with time. Our ability to detect sequence homology in related proteins depends on their divergence rate and evolutionary distance [23]. Using PAM matrix, Dayhoff et al. show that the limitation of sequence identity for deducing protein homology is around 20% identity [23]. If two proteins share less than 20% sequence identity, it means either they are not homologous proteins or their common origin is obliterated in evolution.

There are two possible evolutionary scenarios for microbial rhodopsins and metazoan rhodopsins: (1) using retinal as chromophore, binding retinal with a lysine and similar seven-transmembrane domain are the result of convergent evolution (2) their common features are the legacy of a common ancestor, yet their sequence identity is hardly detectable because of the quick and/or longtime divergence.

To investigate the evolutionary relationship between microbial rhodopsins and metazoan rhodopsins, we have to bypass the problem of lacking sequence similarity. Fitch developed a statistical method to distinguish homologous proteins from nonhomologous ones [24]. His method compares the ancestral state from one protein group with the ancestral state from another. It circumvents the need of sequence identity to decide the evolutionary relationship between two groups of proteins. In this study, we used his method to test whether microbial rhodopsins and metazoan rhodopsins are homologous proteins or not.

2. Materials and Methods

2.1. Structure Data

A direct search in PDB database came back with two metazoan rhodospins and five microbial rhodopsins with structure data (Table 1).

2.2. Sequence Data

The whole genome protein sequences and corresponding cDNA sequences for twenty-seven metazoan species were downloaded from Ensembl database, NCBI database, and VectorBase [25]. These species cover seven phyla—Porifera, Cnidaria, Nematoda, Arthropoda, Chordata, Hemichordata, and Echinodermata. The species in Chordata also represented major classes in this phylum. We used a Perl script to extract the longest transcripts for each genome in this study.

2.3. BLAST and FASTA Search for Rhodopsin Genes in Genome Data

We used BLAST to search for rhodopsin genes in microbial genomes [26]. Using five microbial rhodopsins with structure data as queries, we searched the complete microbe genome database, fungi genome database, and green algae genome database on NCBI website. The BLAST parameters were set as follows: max target sequences were 500, expect threshold was 0.001, and the others were default.

We used FASTA 3.5 to search for rhodopsin genes in each metazoan genome [27]. Two metazoan rhodopsins with structure data served as queries. The E-value for FASTA search was set as 0.001.

Hits in BLAST or FASTA search result were aligned back to query sequences using MUSCLE with default parameters [28]. The hits were identified as candidate rhodopsins only when they share a conserved retinal-binding lysine in the seventh helix as the same position as queries. We removed redundant candidate hits and any sequence shorter than 200 amino acids or longer than 1000 amino acids.

2.4. Structure Alignment

Using their PBD files, two metazoan rhodospin protein structures and five microbial rhodopsin protein structures were aligned with CE-MC multiple protein structure alignment server with default parameters [29].

2.5. Sequence Alignment

Microbial or metazoan rhodopsin protein sequences were aligned using MUSCLE with default parameters [28]. All nucleotide sequences in this study were aligned according to their protein sequence alignment result.

2.6. Test Region Selection

Although there is no clearly detectable sequence identity, protein structure is something comparable between microbial and metazoan rhodopsins. The selection of test region between microbial and metazoan rhodopsins was based on their structure alignment. The problem we encountered here is that structure data are far scarcer than sequence data in both groups of rhodopsins. Only two metazoan rhodospins and five microbial rhodopsins have structure data. So we have to use their structure alignment as a guide to infer seven-transmembrane domain in their sequence alignment.

All microbial rhodopsins share a clearly detectable sequence homology as well as all metazoan rhodopsins, so sequence alignment result is reliable within microbial or metazoan group. However, structure alignment result does not always coincide with sequence alignment result that is, the positional homology proposed by microbial structure alignment may not be the same one proposed by microbial sequence alignment. Our solution is that we first aligned all microbial rhodospin sequences using MUSCLE. Then we picked out five microbial rhodopsin sequences with structure data in MUSCLE alignment result and compared their sequence alignment with their structure alignment. By doing so, we could identify the positional homology agreed by both alignment methods. We repeated this practice in metazoan rhodopsins using squid and bovine rhodopsins’ structure alignment as a guide. The final test region is the alignment result agreed by both structure and sequence alignments.

2.7. Phylogenetic Analysis and Ancestral State Inference

Neighbor-joining, Bayesian, and maximum-likelihood methods were used to construct phylogenetic tree for microbial or metazoan rhodopsins. ProtTest was used to select evolution models for our phylogenetic analyses [30]. MEGA 5 was used to construct NJ tree with “pairwise deletion” option and “JTT” model [31]. Rates and patterns were set as “Gamma Distributed”, and Gamma parameter was set as “4”. Bootstrap method was used to test phylogeny, and number of bootstrap replications was set as “500”. PhyML 3.0 was used to construct ML tree with “WAG” model [32]. Proportion of invariable sites and gamma shape parameter were estimated from alignment result. Approximate likelihood-ratio test was used to test for branch reliability [33]. MrBayes 3.1.1 was used to construct Bayesian tree with “WAG” model [34]. We ran for 500,000 generations and sampled posterior probability trees every 1000 generations. We summarized 25% of both parameter values and trees to get the consensus tree.

PHYLIP package was used to construct Fitch-Margoliash tree for rhodopsin genes within each metazoan species [35]. Within-species rhodopsin tree was built with “JTT” model and tested with 100 bootstrap replicates.

Phylogenetic trees served as the evolutionary history for our ancestral state inference. Parsimony method was used to infer ancestral states [24]. We wrote a Perl script to implement this method.

2.8. Test for Relatedness in Ancestral States

The test for relatedness in two ancestral states is a statistic method Fitch devised in his 1970 paper [24]. The basic idea behind this test is that the probability of relatedness can be calculated by comparing the observed mutation distance between two ancestral states with the expected mutation distance between them. The observed mutation distance is the actual nucleotide differences between two ancestral states. The expected mutation distance between two ancestral states is the probability of randomly chosen disjoint nucleotide sets between them multiplied by the length of their sequence. The standard deviation between two distances is the square root of expected distance multiplied by the probability of randomly chosen intersectant nucleotide sets between them. The number of standard deviations between the observed mutation distance and the expected mutation distance follows normal distribution. The probability of its value could be found in the table of normal probability and it is used as the probability of significance.

3. Results

3.1. Structural Homology between Microbial Rhodopsin and Metazoan Rhodopsin

The structure alignment of five microbial rhodopsins and two metazoan rhodospins shows that all rhodopsins share a remarkable structural homology (Figure 1). Seven-transmembrane helices are conserved within microbial or metazoan rhodopsins and between them. Although there is no clearly detectable sequence homology between these two groups of rhodopsins, the structure alignment reveals that they share a conserved WXXY sequence motif in the sixth helix. Interestingly, the lysine that binds retinal in the seventh is not structurally conserved and locates in different position between them. There is also an/a insertion/deletion in the seventh helix between these two groups of rhodopsins, which is just one amino acid before the crucial lysine in microbial rhodopsins (insertion) or one amino acid after the crucial lysine in metazoan rhodopsins (deletion). So the position of retinal-binding lysine shifts three amino acids forward in metazoan rhodopsins.


Structure alignment of squid rhodopsin (2Z73:A|PDB, metazoan rhodopsin), bovine rhodopsin (1U19:A|PDB, metazoan rhodopsin), Anabaena sensory rhodopsin (1XIO:A|PDB, microbial rhodopsin), Natronomonas sensory rhodopsin II (1GU8:A|PDB, microbial rhodopsin), Halobacterium salinarum bacteriorhodopsin (1JV6:A|PDB, microbial rhodopsin), Natronomonas halorhodopsin (3A7 K:A|PDB, microbial rhodopsin), and Salinibacter ruber xanthorhodopsin (3DDL:A|PDB, microbial rhodopsin). Squid rhodopsin is used as the template for delineating seven-transmembrane helices. Shaded residues are structural homologues. Conserved tryptophan and tyrosine in WXXY motif are marked with black asterisks. The retinal-binding lysine is in bold style and boxed. The aspartic acid in microbial rhodopsin corresponding to the retinal-binding lysine in metazoan rhodopsin is in bold style and underlined. The test region is marked with thin lines.
3.2. Rhodopsin Genes in Microbial and Metazoan Genomes

BLAST search for microbial rhodopsins came back with 62 microbial rhodopsins (See Table S1 in Supplementary Material available online at http://dx.doi.org/10.1155/2013/435651). FASTA search for metazoan rhodopsins came back with 227 metazoan rhodopsins from 25 species (Table 2).

In 62 microbial rhodopsins, thirty-five of them are from bacteria, twenty-four are from archaea, and three are from eukaryotes. Bacterium Salinibacter ruber M8 and archaea Haloarcula marismortui ATCC 43049 have four different copies of rhodopsin gene. One bacterium species and four archaea species have three different rhodopsin genes. Eleven microbial species have two different rhodopsin genes. Among three eukaryotic microbial rhodopsins, two of them are from single-celled green alga Chlamydomonas reinhardtii and one is from encapsulated yeast Cryptococcus neoformans var. neoformans.

Table 2 shows the number of rhodopsin genes in each metazoan species. We named rhodospin genes in numeric order within each metazoan species. The number of rhodopsin genes varies drastically in each metazoan species. In insects, malaria mosquito has nine rhodopsin genes while body blouse only has three. There is no rhodopsin gene found in sponge Amphimedon queenslandica and nematode Caenorhabditis elegans, although they do have rhodopsin-related genes.

3.3. Final Test Region

The final test region we selected is the consistent alignment result between structure and sequence alignments. There is no consistent region found in helices A, B, or D. In helix C, there is an 18-amino acid consistent region. In helix E, there are two consistent regions: one is 11 amino acid long and the other is 14 amino acid long. In helix F, there is a 25-amino acid consistent region. In helix G, there is an 18-amino acid consistent region. The total test region is 86 amino acid long and equals 258 nucleotides.

3.4. The Evolutionary History and Ancestral State Inference in Metazoan Rhodopsins

We used three different methods to construct phylogenetic trees for all metazoan rhodopsins in this study. Hydra rhodopsins serve as an outgroup to root metazoan trees. In our study, Hydra is the only animal from Cnidaria. It is the basal phylum to Arthropoda, Chordata, Hemichordata, and Echinodermata. Rooted with Hydra rhodopsins, three trees show three different overall topologies. Neighbor-joining tree shows all rhodopsin genes divided into three major clades except Hydra rhodopsins (Supplemental Figure 1). One clade mainly consists of chordate rhodopsins and no arthropod rhodopsins. The other two clades contain both chordate and arthropod rhodopsins. Maximum-likelihood tree shows a different evolutionary history from NJ tree (Supplemental Figure 2). ML tree has four major clades instead of three. Bayesian tree shows a more complicated evolutionary history (Supplemental Figure 3). Three separate clades in NJ tree are mixed in Bayesian tree. We did not know which tree is the most reliable one in all three trees. Three trees produced three different ancestral states. Only one state is true, because all metazoan rhodopsins share only one evolutionary history.

In order to get reliable ancestral state, we constructed the phylogenetic tree for rhodopsins within each metazoan species instead of for all metazoan rhodopsins (Figures 2(a) and 2(b)). By reducing the number of taxa in tree construction, we could get more reliable trees for ancestral state inference. Nevertheless, by doing so, we had to infer one ancestral state for each metazoan species. Using one Hydra rhodopsin as an outgroup, we constructed 24 metazoan rhodopsin trees and inferred 24 ancestral states based on these trees. Eighteen of them are possible metazoan rhodopsin’s ancestral states in Chordata. Four of them are possible ancestral states in Arthropoda. Two of them are possible ancestral states in Hemichordata and Echinodermata.


(a)
(b)
(a)
(b) (a) Fitch-Margoliash tree for all rhodopsin genes in human. (b) Fitch- Margoliash tree for all rhodopsin genes in chicken. Hydra rhodopsin gene serves as outgroup. The numbers adjacent to tree nodes are bootstrap values. The tree node where ancestral state is built on is marked with a filled black square
3.5. The Evolutionary History and Ancestral State Inference in Microbial Rhodopsins

We also used three different methods to construct phylogenetic trees for all microbial rhodopsins. Three microbial trees are consistent in overall topologies, although they differ in the position of one branch which contains six bacteria rhodopsins (Supplemental Figures 4, 5, and 6). The problem is that bacteria and archaea are sister clades in biological systematics. It means that we are unable to root microbial trees. If we could not decide an outgroup for microbial trees, we would not be capable of inferring any ancestral state with them.

To overcome this problem, we first tried to find which microbial subtree is the most possible candidate tree for ancestral state inference. Using Fitch’s method, we tested each extant microbial rhodospin gene with 24 metazoan ancestral states. We found that three microbial rhodopsins are distantly related to metazoan ancestral states with statistical significance (Supplemental Table 2). These three rhodopsins are all located in one single subtree which contains 13 microbial rhodopsins (Figure 3). Then we inferred all possible microbial rhodopsin’s ancestral states on this subtree.


Unrooted Bayesian tree for all microbial rhodopsin genes. The numbers adjacent to the nodes are posterior probability values. The length of branch reflects evolutionary divergence. Microbial rhodopsin genes distantly related to metazoan rhodopsin’s ancestral states (>95% quantile) are marked with a filled black triangle ▲. The tree node where microbial rhodopsin’s ancestral state is built on is marked with a filled black square
3.6. The Relatedness between Microbial Rhodopsins’ Ancestral States and Metazoan Rhodopsins’ Ancestral States

We tested 24 metazoan rhodopsin’s ancestral states with all possible microbial rhodopsin’s ancestral states on the candidate subtree. Among all inferred microbial rhodopsin’s ancestral states, one microbial rhodopsin’s ancestral state has the smallest mutation distance with metazoan rhodopsin’s ancestral states (Figure 3). This microbial ancestral state is reconstructed upon one fungi rhodopsin, one bacteria rhodopsin, and eight archaea rhodopsins. Test result shows that 13 metazoan rhodopsin’s ancestral states are divergently related to it with statistical significance (Table 3). These ancestral states cover Arthropoda, Chordata, Hemichordata, Echinodermata, and two subphyla in Chordata—Tunicata (sea squirt) and Cephalochordata (amphioxus).

mutations in the first and second codon positions.

4. Discussion

4.1. Structural Homology versus Common Origin

Microbial rhodopsins and metazoan rhodopsins share a remarkable structural homology in their seven helices (Figure 1). However, the structural homology does not necessarily indicate the common origin. The empirical view of common origin is based on sequence homology. Convergent evolution is also a probable cause for structural homology [36]. Through both structure alignment and sequence alignment, we found that the vast majority of microbial and metazoan rhodopsins share a conserved WXXY sequence motif in the sixth helix. The tryptophan and tyrosine in this motif are crucial amino acids which form retinal-binding pocket in both groups of rhodopsins [37–41]. The conservation of WXXY motif in both groups of rhodopsin can be explained by either convergent evolution or common origin. In this case, common origin seems to be more plausible than convergent evolution. According to PAM matrix, tryptophan is the least mutable amino acid and tyrosine is the fifth-least mutable amino acid [23].

4.2. The Convoluted Evolutionary History of Metazoan Rhodopsins

There is only one rhodopsin gene found in acorn worm while there are 35 rhodopsin genes found in zebra fish. No rhodopsin gene found in sponge and nematode indicates that rhodopsin is not essential for the survival of metazoa. However, photoreception capability does grant animals a great advantage for their survival. Nonessentiality and advantage for survival render the evolution of metazoans rhodopsins a birth-and-death process, in which gene duplication event creates new genes and some newly-created genes are kept in genome while others vanish from genome by accumulating deleterious mutations [42]. This process led to the various number of rhodopsin genes in different metazoan species for example, body louse has three different rhodopsin genes while malaria mosquito has nine, and both of them are insects. It also made divergence and subfunctionalization rampant among duplicated rhodopsin genes. There are at least ten different subgroups of metazoan rhodopsins, and only one subgroup directly functions as visual opsins [11, 18–21]. The birth-and-death process produced a very complicated evolutionary history for metazoan rhodopsins. Due to their convoluted evolutionary history and the large number of sequences used in phylogenetic analysis, we could not acquire an accurate phylogenetic tree for all metazoan rhodopsins. So in ancestral state inference, we used each species’ rhodopsin genes to perform phylogenetic analysis in order to build a reliable tree within each metazoan species.

4.3. Gene Duplication and Horizontal Gene Transfer in Microbial Rhodopsins

Gene duplication and horizontal gene transfer are common in microbial rhodopsins. Two microbial species have four rhodopsin genes, five species have three rhodopsin genes, and eleven species have two rhodopsin genes (Supplemental Table 1). Both of the gene duplication and horizontal gene transfers contribute to multiple rhodopsin copies in these species. For example, bacterium Salinibacter ruber M8 has four rhodopsin genes. Its two sensory rhodopsins (Bac_Sal_s1 and Bac_Sal_s2) were the result of a gene duplication event, but they are clustered with archaea rhodopsins in microbial tree. It means that Salinibacter ruber M8 got its original sensory rhodopsin from archaea through horizontal gene transfer. Horizontal gene transfer makes the origin of microbial rhodopsins untraceable. The fact that all three domains of life have microbial rhodopsins proposes that microbial rhodopsin is a very ancient gene. It could be as old as life itself.

4.4. Are Metazoan Rhodopsins and Microbial Rhodopsins Homologous Genes?

The main purpose of this study is to answer the question: are metazoan rhodopsins and microbial rhodopsins homologous genes? Due to the lack of direct evidence—sequence homology, we tried to answer this question by comparing their ancestral states. The complicated evolutionary history of metazoan rhodopsins made a reliable overall phylogenetic tree hardly possible. We circumvented this problem by building the phylogenetic tree for metazoan rhodopsins within each species. Then using these reliable trees, we inferred one ancestral state for each metazoan species.

In our 24 metazoan rhodopsin’s ancestral states, more than half of them are divergently related to the microbial rhodopsin’s ancestral state with statistical significance and less than half of them without statistical significance (Table 2). There are two possible explanations for the reason why the other 11 metazoan rhodopsin’s ancestral states show no statistical significance:

the birth-and-death process eliminated some basal metazoan rhodopsins in these species. Therefore, their phylogenetic trees only allowed us to trace back to a recent ancestral state instead of a much more ancient one

in these species, the existent metazoan rhodopsins diverge from their ancestor so greatly that there is no traceable information left in their sequences. These two explanations are not mutually exclusive.

For thirteen metazoan rhodopsin’s ancestral states divergently related to the microbial rhodopsin’s ancestral states with statistical significance, does it mean that metazoan rhodopsin and microbial rhodopsin are homologous genes? By the definition of Fitch’s test, the answer is yes. The test region we selected is total 86 amino acids. Within test region, the average mutation distance between existent metazoan and microbial rhodopsin is mutations in the first and second codon positions. Assuming one mutation in the first or second codon position would change its coding amino acid, each paired codon in the test region averagely shares about 1.38 mutations between two rhodopsin groups. It explains why we cannot find clearly detectable sequence homology between microbial and metazoan rhodopsins. After ancestral state reconstruction, the shortest mutation distance between microbial and metazoan ancestral states was 63 mutations. It is found between chicken and one microbial ancestral state inferred on nine microbial rhodopsins, with a

value of 0.0045. There are total 86 amino acids in the test region. If mutations were evenly distributed in each codon, there would be 63 amino acid differences between microbial and metazoan ancestral states. In another words, the sequence identity between microbial and metazoan ancestral states would be 23 amino acids. 23 divided by 86, it is about 26.7% sequence identity.

In pairwise sequence alignment, over 30% sequence identity is the safe standard for homologous proteins. Proteins sharing from 15% to 30% sequence identity are in the twilight zone, which means their homologous status is still in ambiguity [22]. Even when tracing back in time by reconstructing ancestral states, our result shows that only 26.7% sequence identity might exist in four helices between ancestral microbial and metazoan rhodopsins. In conventional viewpoint, such result still cannot prove that metazoan and microbial rhodopsins are homologous proteins. Using Hydra rhodopsin as an outgroup, we can only infer metazoan ancestral rhodopsin states as early as in bilaterian ancestors. Fossil records show that the earliest bilaterian animal appeared about 580 million years ago [43]. However, based on the estimation of nuclear genes, early metazoan divergence can be traced back to 830 million years ago [44]. There is no rhodopsin gene found in sponge, and the closest microbe species related to Metazoa in this study is fungus Cryptococcus neoformans var. neoformans. So we have at least 250-million-year divergence time between microbial and metazoan ancestral states. Such longtime divergence could explain the low sequence identity between microbial and metazoan ancestral states. Certainly, the low sequence identity could also be seemingly explained by convergent evolution, which means rhodopsin gene appeared independently in microbes and Metazoa. But our result shows that ancestral microbial rhodopsins and ancestral metazoan rhodopsins shared about 26.7% sequence identity in four helices. It is implausible to believe that random mutations would create an almost identical structure by generating long strings of amino acids with similar sequences.

4.5. The Position of Retinal-Binding Lysine in the Seventh Helix

The structure alignment of microbial and metazoan rhodopsins shows an intriguing phenomenon: although both groups of rhodopsins have a retinal-binding lysine in the seventh helix, the position of this lysine is not structurally conserved between them (Figure 1). Its position shifts three amino acids forward in metazoan rhodopsins. Once again the different position of retinal-binding lysine could be simply explained by convergent evolution. However, most microbial rhodopsins have an aspartic acid in the position where metazoan rhodopsins have a retinal-binding lysine. In microbial rhodopsins, this aspartic acid functions as a part of counterion which balances the positive charge of retinal-binding lysine [45, 46]. Since structure alignment and ancestral state tests suggest that microbial and metazoan rhodopsins are homologous proteins, it means that this negatively charged aspartic acid in microbial rhodopsin mutated to the positively charged retinal-binding lysine in metazoan rhodopsin. The genetic code for aspartic acid is GAC or GAT while the genetic code for lysine is AAG or AAA. These two amino acids share the same adenine at the second codon position. The second codon position tends to have the slowest mutation rate among three codon positions [47]. It is probable that Asp (GAC or GAT coding) first mutated to Asn (AAC or AAT coding) and then Asn mutated to Lys (AAG or AAA coding) during the evolution of rhodopsin gene.

The retinal-binding lysine in the seventh helix is the most crucial amino acid for rhodospin’s photoreception function. It binds the chromophore retinal which is responsible for light absorption [1, 2]. If microbial and metazoan rhodopsins are homologous proteins, their retinal-binding lysine at different positions means that the function of photoreception was once lost during the evolution of rhodopsin gene. In metazoan rhodopsin, rescue mutation of this lysine salvaged the function of photoreception in metazoan rhodopsin. The once-lost lysine explains why there is no clearly detectable sequence homology between microbial and metazoan rhodopsins. During the evolution from single-celled organisms to multicellular animals, the rhodopsin gene in early metazoan ancestor lost retinal-binding lysine and therefore lost its function of photoreception. Loss of function freed the rhodopsin gene from functional constraint, and the process of divergence quickly changed its original sequence beyond recognition. Inexplicably in the later metazoan evolution, one of those loss-function rhodopsin genes managed to retrieve a lysine in its seventh helix through random mutation and therefore rescued its function of photoreception.

5. Conclusion

Based on our analysis, we propose that microbial and metazoan rhodopsins are homologous proteins and the function of photoreception was once lost during the evolution of rhodopsin gene. This conclusion may be controversial under the conventional view for homologous proteins. Logically, the view that microbial and metazoan rhodopsins are homologous proteins is the most parsimonious one. It does not require another protein to be the precursor of metazoan rhodopsins. Nature just recycled seven-transmembrane-helix protein for photoreception. However, the alternative view that the nearly identical structure between microbial and metazoan rhodopsins is the result of convergent evolution requires random mutations to create seven-transmembrane-helix domain twice through generating long strings of amino acids with similar sequences. Seven-transmembrane-helix domain does perform other functions than photoreception in Metazoa [48]. They form a large protein family of G-protein-coupled receptors which include metazoan rhodopsin and olfactory receptor. Research shows that most of these seven-transmembrane receptors share a common origin [49]. It is natural for someone to wonder what was the origin of all these seven-transmembrane receptors. There is no ancient seven-transmembrane receptor other than microbial rhodopsins which could be as old as life itself. For those who believe that the identical structure between microbial and metazoan rhodopsins is a result of convergent evolution, they will have to answer such two questions: what was the precursor for all seven-transmembrane receptors in Metazoa if such a precursor existed, how could random mutations shape it into seven-transmembrane helices through generating long strings of amino acids which are also similar to a subset of microbial rhodopsins? On the other hand, our ancestral state inference failed to provide a decisive sequence identity between microbial and metazoan ancestral rhodopsins. The ambiguous sequence identity could be explained by once-relieved functional constraint and the long divergence time between microbes and metazoa. The divergence-time gap might be filled by using rhodopsin-related genes from basal animals for ancestral state inference. The future genome projects for basal animals could hold the ultimate answer to the question of the evolutionary relationship between microbial rhodopsin and metazoan rhodopsin.

Acknowledgments

The authors thank Dr. Xun Gu (Fudan University and Iowa State University) for his research suggestions in this research. This research was supported by grants from the National Basic Research Program (2012CB944600), Ministry of Science and Technology (2011BAI09B00), and National Science Foundation of China (30890034).

Supplementary Materials

Supplemental table 1: Rhodopsin genes identified in microbial genomes.

Supplemental table 2: Microbial rhodopsin gene divergently related to metazoan rhodopsin's ancestral states and how many metazoan rhodopsin's ancestral states it is related to. Here 95% quantile = 15.25.

Supplemental figure 1: Neighbor-joining tree for all metazoan rhodopsin genes. It is based on JTT model and 4 Gamma parameters. The numbers adjacent to tree nodes are bootstrap values. Hydra rhodopsins serve as outgroup. Green, red and blue clades are three major groups in this tree.

Supplemental figure 2: Maximum-likelihood tree for all metazoan rhodopsin genes. It is based on WAG model and 4 Gamma parameters. The numbers adjacent to the nodes are approximate likelihood-ratio test results. Hydra rhodopsins serve as outgroup. Green, red and blue clades are three major groups according to NJ tree. They are mixed in ML tree.

Supplemental figure 3: Bayesian tree for all metazoan rhodopsin genes. It is based on WAG model and 4 Gamma parameters. The numbers adjacent to the nodes are posterior probability values. Hydra rhodopsins serve as outgroup. Green, red and blue clades are three major groups according to NJ tree. They are mixed in Bayesian tree.

Supplemental figure 4: Unrooted Bayesian tree for all microbial rhodopsin genes. The numbers adjacent to the nodes are posterior probability values. The length of branch reflects evolutionary divergence. Green branch means archaea taxon. Red branch means eukaryote taxon. Blue branch means bacteria taxon.

Supplemental figure 5: Unrooted maximum-likelihood tree for all microbial rhodopsin genes. The numbers adjacent to the nodes are approximate likelihood-ratio test results. The length of branch reflects evolutionary divergence. Green branch means archaea taxon. Red branch means eukaryote taxon. Blue branch means bacteria taxon.

Supplemental figure 6: Unrooted neighbor-joining tree for all microbial rhodopsin genes. The numbers adjacent to tree nodes are bootstrap values. The length of branch reflects evolutionary divergence. Green branch means archaea taxon. Red branch means eukaryote taxon. Blue branch means bacteria taxon.

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Copyright

Copyright © 2013 Libing Shen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


RHODOPSIN

Expression

Retinal rod cells are specialized neurons that function in capturing photons and communicating with secondary neurons about the presence of light. These events are initiated by conformational changes in the light-sensitive pigment, rhodopsin, followed by a biochemical cascade of reactions, termed phototransduction (30, 31). In mammalian retina there are � 8 photoreceptor cells. Rods are highly differentiated cells with outer segments (ROS) containing all components necessary for phototransduction. ROS are composed of stacks of 1000� independent disk membranes surrounded by plasma membrane ( Figure 1 , see Supplemental Materials: Follow the Supplemental Material link on the Annual Reviews homepage at http://annualreviews.org/). The main component of the disk membranes is rhodopsin (㺐% of the membrane's proteins). Opsin, the protein component of rhodopsin, is specifically expressed in retinal rod photoreceptors and in some cells of the pineal gland (37). In adult mice, 0.06% of the total retinal RNA encodes for opsin (photoreceptors constitute ��% of all cells in the retina) (38). This translates into the highest expression of any GPCR. About 0.5𠄱 mg of rhodopsin can be isolated from one bovine retina.

Molecular packing of rhodopsin (A) and sensory rhodopsin (B) in their crystals. One asymmetric unit contains two rhodopsin molecules. The central dimer is shown as a continuous surface, whereas the rest are shown as ribbons. Views are from different crystallographic X-, Y-, Z-axes for rhodopsin (27), and X-, and Z- for sensory rhodopsin. The data for sensory rhodopsin were taken from Protein Data Base (1H68). Coordinates: Models of rhodopsin and the homology models of cone pigments have been deposited in the Protein Data Bank (PDB) (identifiers 1F88, 1HZX, 1KPN, 1KPW, 1KPX).

Purification

The absorption spectrum of rhodopsin in detergent solutions displays two maxima in the UV-Vis region: the protein band around 280 nm and the chromophore-related peak at 498 nm. The ratio of the absorption A280 nm/A498 nm for pure rhodopsin devoid of opsin is 𢏁.6, with an extinction coefficient of 42,000 cm 𢄡 M 𢄡 at 498 nm. Rhodopsin is stable at room temperature for days when extracted into many detergents, including Chaps, dodecyl-β-maltoside, or Tween 80. The most frequent source of native rhodopsin is bovine eyes. Native rhodopsin is initially pre-purified by isolation of ROS from the retina using a sucrose gradient method (50�% rhodopsin content in ROS) [reviewed in (6)]. The purification methods require separation of rhodopsin from contaminating proteins and from bleached opsin. All methods require detergent for rhodopsin solubilization. The first method takes advantage of rhodopsin glycosylation and employs concanavalin A affinity chromatography (39). A large percent of opsin binds irreversibly to the resin. Concanavalin A chromatography is scalable, and large amounts of material can be prepared, although the purified rhodopsin is contaminated with other glycoproteins and with concanavalin A, which leaches from the resin. The second method uses hydroxyapatite chromatography and yields only partially purified protein (40). Rhodopsin is also efficiently purified by immunoaffinity chromatography using Molday's 1D4 monoclonal antibody, which recognizes seven to nine C-terminal amino acids of bovine rhodopsin. This method is particularly useful for heterologously expressed rhodopsin and other visual pigments (26, 41). The fourth method takes advantage of highly enriched rhodopsin in ROS and the instability of opsin and contaminating protein during prolonged incubation in mild detergent in the presence of divalent metal ions (43). It is an effective and scalable method that does not use any chromatographic columns. This method also enriches rhodopsin preparations with native ROS lipids and produces highly concentrated rhodopsin with controllable concentrations of detergent suitable for crystallization studies. This method is not applicable to heterologous systems due to the low expression levels of rhodopsin.

Composition

Rhodopsin is composed of a transmembrane apoprotein, opsin, and 11-cis-retinal bound to the protein through a Schiff base linkage to a lysine side-chain. Bovine opsin (Swiss-Prot: <"type":"entrez-protein","attrs":<"text":"P02699","term_id":"129204","term_text":"P02699">> P02699) is composed of 348 amino acids with a molecular mass of 39,007. The total molecular mass increases to 42,002 when posttranslational modifications are included (palmitoylation, acetylation of N terminus, and glycosylation). The most prevalent amino acids are Phe (8.9%), Val (8.9), Ala (8.3), and Leu (8.0), suggesting a major hydrophobic character for this protein.

Rhodopsin is extensively modified by posttranslational modifications. The chromophore is attached through a protonated Schiff base to Lys 296 (44). The N-terminal Met is acetylated (45), as is found frequently for other eukaryotic proteins at their initiation Met residue. Using ex vivo [ 3 H]-labeling, it was shown that opsin is palmitoylated (46), a modification that is frequently observed among GPCRs. Two Cys residues, Cys 322 and Cys 323 located at the C terminus, are palmitoylated (47). Two Cys residues from helix III and E III (the loop connecting helices IV and V) are cross-linked by a disulfide bond (48). Two (Man)3(GlcNAc)3 groups modify opsin through an asparagine-linkage ( Figure 2 , see Supplemental Materials: Follow the Supplemental Material link on the Annual Reviews homepage at http://annualreviews.org/) at the N terminus (Asn 2 and Asn 15 ) (49). Glycosylation is not homogenous and other, but minor, compositions of the carbohydrate moieties were identified (50). Rhodopsin undergoes a light-dependent phosphorylation on six to seven Ser/Thr residues at the C-terminal end (51). In vivo, there are three sites, Ser 336 , Ser 338 , and Ser 343 , that are phosphorylated by direct and quantitative methods after 20�% bleaching of the protein (52, 53). The phosphorylation processes, at lower bleaches such as 100�,000 photons/s per rod, are not yet accessible to currently available technologies. At these bleach levels, our rods are functional before they saturate at more intense light. Heterogeneity and multiple rhodopsin phosphorylation have been observed in vitro [reviewed in (54)].

Ribbon drawings of rhodopsin. Helices I–VIII are colored as a spectrum of visible light from blue (helix I) to red (helix VIII), and two orientations are shown. Palmitoyl chains and oligosaccharide groups shown using ball-and-stick models.

Rhodopsin, when isolated from ROS, contains variable amounts of tightly bound phospholipids. These lipids possibly stabilize rhodopsin and coat the hydrophobic transmembrane regions of the protein. We found, using radioactive phospholipids, that they can be removed completely only under very harsh conditions, such as 1% SDS in formic acid and trifluoroethanol (1:1) (X. Zhou & K. Palczewski, unpublished data). It is reasonable to speculate that the integrity of rhodopsin and other membrane proteins may be lost by removal of all tightly associated lipids.

Regeneration and Photobleaching Pathway

The key reaction of visual excitation is the ultra-fast (femtoseconds) photochemical reaction of rhodopsin's chromophore, 11-cis-retinal forming all-trans-retinal (55). From a theoretical organic chemistry point of view, this isomerization most likely involves the “Hula-Twist” mechanism that preserves, at first approximation, the positions of theβ-ionone ring and the Schiff base (56). A conventional “one-bond-flip” mechanism would predict a large rotation of the β-ionone ring within the rhodopsin molecules ( Figure 3 , see Supplemental Materials: Follow the Supplemental Material link on the Annual Reviews homepage at http://annualreviews.org/). In milliseconds, the signaling Meta II is established and this catalytically active form of rhodopsin binds and activates transducin (T, Gt).

Two-dimensional model of bovine rhodopsin. Buried residues are shown in gray. Orange, red, and violet denote surface residues. Residues in contact with polar headgroups of the membrane on the cytoplasmic side are orange. Similar residues on the extracellular side are red. All other surface residues are violet.

The photoisomerization of 11-cis-retinylidene to all-trans-retinylidene triggers conformational changes of opsin through multiple intermediates, such as photorhodopsin, bathorhodopsin, lumirhodopsin, Meta I, Meta II, and Meta III, before the chromophore hydrolyzes and leaves the binding pocket (34). These intermediates are short-lived, but can be trapped by low temperature and distinguished by specific absorption maxima in the range of visible light (57). The final steps, namely hydrolysis of all-trans-retinylidene and its relation to Meta III, are poorly understood at the mechanistic level. The hydrolysis of the Schiff base appears to be the rate-limiting step in the release of the chromophore (58). In addition, two forms of Meta II were identified, Meta IIa and Meta IIb, that differ in the protonation state at the cytoplasmic surface, whereas the Schiff base is deprotonated with a characteristicλmax at 380 nm (59). The transducin-activating form is Meta IIb (34).

Free all-trans-retinal also binds to opsin and forms partially active receptors toward activation of transducin [reviewed in (60)]. This activity is enhanced compared with the activity of free opsin. From the crystallographic model, a potential binding site for the retinal has been identified in the hydrophobic domain of rhodopsin (D.C. Teller, unpublished data). For 11-cis-retinal, binding to this site could be the first step in the regeneration of rhodopsin, before the chromophore binds non-covalently to the retinylidene cavity and prior to stable formation of the Schiff base (61). In the Meta II-transducin complex, all-trans-retinylidene can be photoisomerized back to 11-cis-retinylidene without transducin dissociation, suggesting that the G protein imposes conformational changes on the rhodopsin surface that cannot be reversed even upon photoisomerization (62). However, when Meta II is photolyzed by blue light, a product is formed that has absorption properties similar to that of rhodopsin with λmax at 500 nm, but with all-trans-retinal bound (63). These data indicate that all-trans-retinylidene can be bound in the transmembrane segment of rhodopsin in two distinct conformations: one that activates the opsin moiety and another that inactivates it.

Mutagenesis

Availability of rhodopsin sequences and development of molecular biology techniques have had tremendous impacts in probing rhodopsin structure using muta-genesis and biochemical approaches. Findings from this research are discussed in the subsequent paragraphs, where they strengthen observations and interpretation of rhodopsin's structure and function.

A general method for rhodopsin expression and purification from monkey (or human) kidney cells (64), insect cells (65), and different yeast strains (66, 67) was introduced. In particular, we benefited from these studies in understanding the spectral tuning of rhodopsin. Retinals in their Schiff base forms absorb in the near ultraviolet range (360� nm, compared with � nm for retinols). The predicted counterion for the protonated Schiff base has been identified as Glu 113 , which is highly conserved among all known vertebrate visual pigments (68-70). The addition of a proton to the Schiff base, together with critical placement of intramolecular negative charges, results in a bathochromic shift in the absorption spectrum to that characteristic of native rhodopsin (500 nm). The counterion in the hydrophobic environment causes a ∼sevenfold increase in the pKa of the protonated Schiff base. Therefore, rhodopsin in its native environment will have its chromophore in the protonated Schiff base linkage (29).

Glycosylation was shown to be dispensable for the proper folding and function of rhodopsin. Mutant rhodopsins lacking Asn 15 -glycosylation exhibited poor folding and were defective in transport to the cell surface. They were also poor transducin activators, perhaps owing to their intrinsic instability (71). These studies have not yet been extended to mouse animal models.

Ridge et al. pioneered studies of rhodopsin using expressed polypeptide fragments in COS cells. Splitting rhodopsin in the second and third cytoplasmic loops led to production of two-fragment rhodopsins that show properties similar to the wild-type (72, 73). These studies, and earlier limited proteolysis studies [reviewed in (6)], revealed several important aspects of rhodopsin function. For example, connecting subsequent loops II and III have only a small stabilizing effect on rhodopsin, whereas the chromophore is critical for the stabilization of the tertiary structure. It appears that helices I–III and V–VII, with helix IV connected to either of these two fragments, form active rhodopsin, suggesting the existence of two independent intradomain interactions. These data are in agreement with another set of experiments. Rhodopsin retains its spectrum after extensive proteolysis of its exposed loops by pronase in native membranes, or in detergent solutions, albeit, digested rhodopsin is more temperature-sensitive to denaturation (K. Palczewski, unpublished data).


The genetics of microbial rhodopsins and halobacteria

Surprisingly, the entire field of bacteriorhodopsin research managed without any genetic techniques or concepts until the 1980s. Analyses of halobacterial DNA had been carried out in the 1960s (e.g. Moore & McCarthy, 1969), and halobacterial ribosomes had been studied by Donn J. Kushner and colleagues at the Division of Biosciences of the National Research Council (NRC) in Ottawa (e.g. Bayley & Kushner, 1964 Oren, 2002) [due to their stability, the ribosomes of halophiles such as Halobacterium marismortui (now Haloarcula marismortui, see Oren et al., 1990) have played an important role in determining ribosomal structure (e.g. Yonath, 2009)]. These publications did not, however, considerably influence bacteriorhodopsin research. The field developed separately from classical molecular biology and the early years of genetic engineering. Microbial genetics had already been ‘molecularized’ due to the discovery of the double helix structure of DNA in 1953 and by insights into transcription and translation, as well as the emergence of recombinant DNA in the early 1970s ( Morange, 1998). Protein science had also been influenced by structural methods and concepts such as protein crystallography, Pauling's α-helix and the structures of myoglobin and haemoglobin from Cambridge's LMB ( de Chadarevian, 2002). Membrane research (as well as many other fields of the life sciences) adopted a different path of molecularization than bacterial genetics and structural biology. In the case of early bacteriorhodopsin science, the entire research programme – including culturing Halobacterium, preparing the purple membrane, and analysing the structural, biochemical and physiological properties of the protein – was carried out as if Halobacterium were an organism without genes and genetic apparatus.

Several factors could be suspected to lie behind the slow import of genetics into membrane research. First of all, conditions such as the high osmotic strength of the media or the lack of resistance to common antibiotics must have impaired the adaptation of molecular genetic techniques. Yet, in order to understand why molecular research on halophiles could flourish without these technologies, another characteristic of these organisms needs to be taken into account, namely the fact that Halobacterium is extremely phenotypically variable. Colonies change their appearance from different shades of pink, red or orange to white, or from opaque to translucent, depending on conditions such as light or salt concentration, as well as ‘spontaneously’ ( Larsen, 1973 Oren, 2002). In contrast to the problems of taxonomy, the variability of Halobacterium had some advantages for molecular studies. Although it was difficult to isolate, standardize, stock and distribute strains, variants of morphological or physiological traits could be easily obtained by plating or subjecting cultures to freeze–thaw cycles. The strain Halobacterium halobium R1, which was the basis of the isolation of bacteriorhodopsin, was a spontaneous mutant. Stoeckenius's team had initially received a strain of H. halobium from the NRC in Ottawa, where the physiology of the organism had been studied for a long time by Norman Gibbons and colleagues from the Division of Applied Biology ( Murray, 1978). From this stock, the Stoeckenius group simply picked colonies of a deeper red colour and translucent appearance (caused by the lack of gas vacuoles) and used them for their membrane project ( Stoeckenius & Kunau, 1968). Other strains that differed in their amount of bacteriorhodopsin or their stability were then isolated from H. halobium R1 by chemical mutagenesis and screenings ( Stoeckenius et al., 1979). All the bacteriorhodopsin research on these strains could be carried out on the basis of phenotypic traits, without any specification of the genotype or the genetic maps.

The success of the field and the wealth of valuable data generated show that genetics was not needed to study the biochemistry and biophysics of bacteriorhodopsin. Carefully selected, maintained and bred strains produced sufficient amounts of the purple membrane. The lack of gas vacuoles facilitated biochemical purification. Generally speaking, this episode of membrane research could be called ‘molecular biology without genetics’. By this, we mean that knowledge about the actual genetics of the organism was not strictly necessary for its analysis in terms of molecules. However, although bacteriorhodopsin research initially developed more or less independently of and in parallel to molecular genetics, the introduction of genetic techniques in the 1980s changed the field's path of research significantly.

In 1979, the isolation of a large plasmid from H. halobium was reported ( Weidinger et al., 1979). Well-known phenotypic variations, such as the presence of gas vacuoles or the purple membrane, were mapped onto insertions, rearrangements or deletions of plasmid DNA ( Pfeifer et al., 1981). For the first time, a molecular genetic explanation was given for the variability of Halobacterium. Genetic investigation was expanded by H. Gobind Khorana's group at MIT, which had begun to focus on bacteriorhodopsin. The phenotypically detected inactivation of bacteriorhodopsin synthesis was correlated with a transposable element inserted at a specific site in the genome ( Simsek et al., 1982). This discovery was based on the finding by Khorana's group of a specific gene coding for bacteriorhodopsin ( Dunn et al., 1981). Fundamental to this study, which involved cDNA techniques, was the determination of the amino-acid sequence of bacteriorhodopsin. This project was carried out both by Khorana's group and by a team led by the Soviet biochemist, Yuri Ovchinnikov ( Khorana et al., 1979 Ovchinnikov et al., 1979). These early genetic studies were conducted within another period of major molecularly driven change in Halobacterium research. In 1980, Carl Woese and colleagues assigned the genus to the kingdom of archaebacteria, which they had distinguished from eubacteria through sequence homology analyses of rRNA ( Fox et al., 1980). Subsequent phylogenetic studies of Halobacterium produced more detailed evolutionary understanding of the biology of these organisms ( Sapienza & Doolittle, 1982).

By the mid-1980s, research on microbial rhodopsins had undergone many important changes and these proteins were increasingly examined using the tools of molecular genetics. A functional characterization of bacteriorhodopsin by mutagenesis, for example, was among the most important achievements expected from the fusion of microbial rhodopsin research and molecular genetics ( Lo et al., 1984). However, Halobacterium genetics was still lacking some of the tools used in organisms such as Escherichia coli. Because vectors such as phages or conjugative plasmids were not available for Halobacterium, it was impossible to introduce DNA fragments in the form of mutated alleles of rhodopsin genes into the organism's genome. Any mutation studies had to be conducted heterologously in E. coli. The development of shuttle vectors for species of Halobacterium in the late 1980s provided a means for this kind of manipulation ( Lam & Doolittle, 1989).

Tracing the history of microbial rhodopsin research clearly sheds light on the contributions of very different fields to membrane research. Whereas bacteriorhodopsin research had begun with studies of the protein in its crystalline state and was followed only much later by studies of the genetic organization of the organism, other forms of membrane transport research developed differently. The maltose transporter and the lactose and histidine permeases, for example, were discovered in model genetic organisms such as E. coli or Salmonella typhimurium in the 1950s. Consequently, these membrane transporters were known first by their genetic localization and organization on the chromosome. They were then characterized by screening for anomalous phenotypes such as transport deficiency, deregulation or the uptake of other substrates ( Schwartz, 1987 Guan & Kaback, 2006). The actual proteins responsible for physiological functions were isolated and characterized only much later, some not until the 1990s. Crystal structures are only just being published (e.g. Oldham et al., 2007). These parallel tracks of research in membrane transport generally and bacteriorhodopsin specifically began to merge in the 1990s with the advent of more broadly usable recombinant DNA tools, as well as affinity chromatographies and biophysical imaging techniques [other membrane biology techniques, such as SDS gel electrophoresis, were also crucial ( Vinothkumar & Henderson, 2010)].


Discussion

Recently, the rational design of retinal binding proteins has emphasized the importance of active site geometry for forming a protonated Schiff base (18, 19). Successful reengineering of the Cellular Retinoic Acid Binding Protein II required proper orientation of the Lys ε-amino group relative to the carbonyl center of 11-cis-retinal for nucleophilic attack. However, we describe four different Lys positions that are capable of binding retinal (G90K, T94K, S186K, and F293K). Each of these alternative positions forces the Lys to react with retinal from drastically different angles, indicating that ideal Bürgi𠄽unitz and Flippin–Lodge angles are not required for Schiff base formation in rhodopsin. This result is perhaps not entirely surprising, because the Bürgi𠄽unitz and Flippin–Lodge angles were originally described for two molecules that collide in solution, not held in a specific orientation by a protein scaffold.

The Lys mutations may also provide insight into the mechanism of rhodopsin activation. In current models, movement of TM5 and TM6 is related to a corresponding displacement of the β-sheet connecting TM4 and 5 (EL2) (5, 20). In the functional K296A/S186K mutant, the Schiff base is located on EL2. If activation involves the movement of EL2 away from retinal in the binding pocket, there must be considerable plasticity in the active site, such that minor structural rearrangements are easily accommodated by the mechanism leading to the global conformational change for active rhodopsin.

Surprisingly, several second-site Lys mutations suppress the constitutive activity of the K296G and K296A parents ( Fig. 4 ). With the exception of K296A/S186K, the constitutive activity of all of the Lys mutants is reduced to within experimental error of the N2C/D282C host. Second-site mutations that reverse the constitutive activity of a functional rhodopsin are rare. These results are consistent with a model in which a key determinant of constitutive activity is neutralization of charge on the Schiff base counterion residue, Glu113.

The K296G/F293K mutant forms a pigment with 11-cis-retinal and activates transducin, but the activity does not depend on light. The apoprotein form, in contrast, does not activate transducin. Thus, the K296G/F293K mutation suppresses the constitutive activity of the K296G parent and allows the protein to form a protonated Schiff base with retinal, but once retinal is bound, the protein is locked in an active conformation. This behavior is significantly different from that of the previously reported dark-active rhodopsin mutant E113Q/M257Y (21). Individually, the E113Q and M257Y mutations constitutively activate rhodopsin. The double mutant is also constitutively active but, in addition, displays dark activity not seen with either single mutation alone. The dark activity of this mutant likely results from conformational uncoupling of the transducin activation domain and retinal-binding site. In contrast, the K296G/F293K apoprotein is inactive but becomes trapped in an active conformation after binding retinal. In this way, K296G/F293K is reminiscent of the “steric doorstop” mutant T118W described by Kono and coworkers (22). Rhodopsin activates transiently in the process of binding retinal, as if the protein adopts an active conformation while opening to allow the ligand to enter the binding pocket (23 �). In the T118W mutant, changing Thr118 to a bulkier side chain results in a steric clash with the 9-methyl group of the retinal, preventing closure of the binding pocket and trapping the protein in an active conformation. Perhaps the dark activity of the K296G/F293K mutant similarly results from a steric clash due to a slight repositioning of the chromophore.

The K296G/A117K and K296A/A117K mutants deserve comment. Previous mutagenesis studies indicated that an acidic residue (either Asp or Glu) at the 117 position can substitute for the Schiff base counterion (26, 27). Thus, even before the crystal structure of rhodopsin confirmed that Ala117 is one helical turn from Glu113, indirect methods had shown that Ala117 is close to the Schiff base nitrogen. In addition, the E113A/A117E mutant forms a protonated MII intermediate upon exposure to light (28), demonstrating that the 117 side chain is close to the Schiff base nitrogen in both the excited state and the ground (or dark) state of the protein. In the present study, we attempted to move the Schiff base Lys from position 296 in TM7 to position 117 in TM3, but the mutant is incapable of forming a pigment with added 11-cis-retinal ( Fig. 2 ). The inability to form a pigment could simply indicate that the mutant protein does not fold properly. However, in the A117K mutant, the Glu113 counterion may be so close to the Lys ε-amino group that the nitrogen remains protonated, unable to provide a lone pair of electrons for nucleophilic attack on the carbonyl carbon of the retinal. This interpretation is supported by the high yield of protein from the immunoaffinity column, because denatured rhodopsin is usually retained on the column under our purification conditions (29, 30). Close proximity of the Schiff base and Glu113 is also consistent with the loss of constitutive activity in this mutant ( Fig. 4 ) (14).

Is the highly conserved active site Lys residue in TM7 of type I and type II rhodopsins a consequence of convergent evolution due to a shared functional constraint on two unrelated protein families? If so, it should not be feasible to move the active-site Lys to another location in the protein and retain the ability to form a functional pigment with retinal. In fact, we were able to construct multiple functional type II pigments in which the active site Lys is moved to three different positions in different secondary structure elements. Therefore, photosensitive rhodopsin function does not require a Lys-retinal Schiff base linkage in TM7. These results support the homology of type I and type II rhodopsins by demonstrating that the shared Schiff base position is not a product of convergence due to functional constraint.

Evolution has optimized modern type II rhodopsins over millions of years, regardless of whether type I and type II rhodopsins are convergent or divergent. Unlike with the natural rhodopsins, we have made little effort to optimize the function of our mutant constructs, other than the N2C/D282C background mutations that confer some stability to the protein. It is plausible that we could find other compensatory mutations that would improve the function of our mutants. For example, other mutations could suppress the low constitutive activity of K296A/S186K or could red-shift the absorbance maximum of the mutants by 10 nm. It is likewise possible that, say, the K296A/S186K mutant would have no constitutive activity in a different protein background from another species we have tried alternate Lys positions in only one protein from one species. In any case, convergent evolution can access all these potential variants (different protein backgrounds and compensatory mutations). The fact that our crude mutagenesis found functional alternative Lys locations so easily𠅊nd that evidently nature has not𠅏urther underscores the implausibility of evolutionary convergence to the same Lys location in helix seven.

In summary, we have tested the hypothesis that the function of rhodopsin (in terms of binding retinal, formation of a long-wavelength pigment, and activation of transducin) constrains the active-site Lys to a location in TM7. The mutants clearly demonstrate that rhodopsin can retain function when the Lys is moved to a different location. These results support a divergent evolutionary scenario in which a common ancestor gave rise to the modern retinylidene proteins. One might wonder why the active-site Lys has not migrated to other locations during divergent evolution. Relocating the Lys would likely require an intermediate either with no active-site Lys or with Lys residues at both locations. Perhaps the Lys has been retained in TM7 because neither of these intermediates is capable of forming a viable pigment.


Evolution: do the eyes have it?

Charles Darwin expressed wonder at the eye and pondered if it could not be explained by evolution by natural selection, then his theory would be declared false. Since then much has been written on scenarios for evolution of the eye. In the mollusks there is represented a very plausible series of eyes that might correspond to stages in evolution from pin-hole camera in the nautilus to the camera eye of octopus that rivals in complexity the vertebrate eye. The eye has come up again in debates on Intelligent Design.

Darwin's Black Box takes up the challenge (Behe 1996). While conceding that anatomical eye evolution can be accounted for by gradual evolution, the author concludes that the sequence of reactions required to convert absorption of photons by rhodopsin into a nervous impulse and restore rhodopsin is an example of irreducible complexity. Perhaps Behe's book is misleading in suggesting that the reaction sequence in eyes had to evolve from scratch, because similar pathways exist for other sensory-neural pathways however, Behe no doubt would contend that an antecedent pathway would still leave the origin of the first complex sensory pathway to be explained and that it would be irreducibly complex.

Critics of Intelligent Design claim that the vertebrate eye shows poor design, compared to the octopus eye, because light in the former must pass through ganglion cells before reaching the photoreceptor cells at the back of the retina, whereas the latter has photoreceptors at the front of the retina, directly in the light path. Skeptics might suggest that poor design means no God or one that leaves secondary causes to finish His work for Him. It seems overly speculative to suggest that, therefore, man, the presumed crown of creation, was short-changed because he does not see as well as the octopus.

Eye Evolution and Genetics

In addition to the camera-like eyes seen in cephalopod mollusks, such as octopus, and in vertebrates, visual organs also include the familiar compound eyes of insects and other arthropods. Looking at the evolution of eyes in living organisms, some one-celled organisms have well developed light sensors, and eyes appeared soon after evolution of the animal kingdom. Curiously, even some box jellyfish (Phylum Cubozoa) of the primitive radially symmetrical group have eyes with well developed lenses (Nilsson et al. 2005). Eyes appear in the bilaterally symmetrical animals in the protostome invertebrate branch, including the Phylum Arthropoda (jointed leg animals), Annelida (segmented worms), and Mollusca (bivalves, snails, and cephalopods). Of course, eyes are characteristic of the vertebrates in the deuterostome group.

In a book devoted to the subject of eye evolution, Andrew Parker (2003) suggested that the sudden ability to see was the spark for the Cambrian Explosion, but he was taken to task by Simon Conway Morris (2003a). Conway Morris stated that eyes evolved many times over many steps. If Parker is correct then the eye evolved early in the Cambrian, and then it triggered an extremely rapid evolution in various phyla, the largest of which all exhibit eyes. According to Parker, the fossil record indicates that image-forming eyes probably evolved first in the arthropods, probably trilobites (Parker 2003). In most phyla, although simple photoreception is almost universally present, no eyes evolved, but eyes evolved later in Annelida, Mollusca, Onychophora, and Chordata. Conway Morris sees eyes as a factor, but not an especially important factor in the rapid evolution in the early Cambrian.

Two views have been held in regard to eye evolution. Gehring (2005) is a leading advocate of a single origin (monophyletic origin) of much of the eye-building genetic apparatus with subsequent divergent evolution. In support of a single origin of eyes is genetic data that shows that a mammalian gene can cause eyes to form in insects. According to this divergence model, one or a few ancestral "eye genes," for example the regulatory gene Pax6, evolved in the ancestral bilateria, resulting in the first eyespot. The ancestral eye then evolved into the various camera-type eyes (probably independently) and various compound eyes. Eyeless phyla are therefore degenerate or failed to develop eyespots further.

The second view exposes multiple origins for eyes (polyphyletic origin). A more basic set of genes allowed multiple origins converging on a few basic eye types. On the basis of molecular phylogeny, other researchers (Oakley and Cunningham 2002) have shown that the paired compound eyes of some seed shrimp evolved within an otherwise eyeless group of Ostracoda. The eyes of other Crustaceans, notably the Malacostraca (crabs, crayfish, lobsters) evolved independently. According to this convergence view, the ancestral animal had a number of genes, including regulatory genes and opsin genes, and that the key factor in eye development was not the presence or absence of genes, but a balance of many genes variously recruited to form the camera type eye independently in three or four distinct lineages and compound eyes in several lineages independently (Conway Morris 2003b).

Fernald (2006) gives an overview of eye evolution from a genetic standpoint, discussing the three protein families most associated with eyes: opsins, crystallins, and regulatory genes that code for transcription factors. The octopus and the vertebrate common ancestor occurred about 750 million years ago. About 70% of eye genes are commonly expressed in vertebrates and octopus, and 97% of these are estimated to have occurred in the ancestral bilaterian. He stated that 875 genes were conserved which might have a common regulatory network recruited at least twice. Vertebrates use ciliary opsin in photoreceptor cells, whereas invertebrates use rhabdomeric opsin. Fernald stated that certain transcription factors have been regularly recruited to build eyes. "The use of homologous genes to build nonhomologous structures may be at the heart of understanding eye evolution and evolutionary processes more generally." Eyes may have evolved independently 40 or more times (Fernald 2006, p. 1917).

The ciliary opsins of vertebrates can be introduced by the well studied function of rhodopsin found in the photoreceptors called rods. Light passes through the inner segment connected by modified cilia to the outer segment which has stacks of membranes. The membranes are studded with many copies of the protein opsin, each attached to a molecule of 11-cis retinal. Retinal absorbs light and changes shape, causing a shape change in opsin, leading to a nervous impulse being transmitted to the brain. Retinal must be converted back to its original shape before it can absorb more light. Cone opsins also have retinal but differ from rhodopsin and each other by a few amino acids in their sequence.

Human cone opsins maximally absorb red at 558 nm, green at 531 nm, and blue at 419 nm. Okano et al. (1992) found that the chicken retina contains four cone opsins and rhodopsin. Chicken red absorbs at 571 nm, green at 508 nm, blue at 455nm, and violet at 415 nm. Chicken green is similar to vertebrate rhodopsins absorbing a wavelength of 500 nm. They suggested that the ancestral opsin evolved from gene duplications into four opsins, as represented in chicken. Vertebrate rhodopsins diverged from green cone opsin later, after the divergence of the ancestral pigment into four groups. Animals had acquired ability to see color at least at the stage of the lowest vertebrates, but later most mammals lost color vision.

Yokoyama (1997) described site specific amino acid sequence changes that change wavelength specificity in opsins. The article also described the dichromatic cone vision of new world monkeys normally resulting from two different opsin genes. Old world monkeys are trichromatic. Human red opsin evolved from green opsin by three amino acid changes.

Arendt et al. (2004, p. 869) reported the discovery of a ciliary opsin in an invertebrate, the ragworm Platynereis. This worm has rhabdomeric opsin in its retina, as expected for an invertebrate, but ciliary opsin, similar to that of vertebrates, in its brain. The authors stated that "any feature specifically shared between them as a result of their common evolutionary heritage necessarily existed in . the last common ancestor of all animals with bilateral symmetry." This opsin is expressed in ciliary structures in the brain. They believe that r-opsins in vertebrates persisted in retinal ganglion cells.

Bellingham et al. (2006) reported the discovery of a melanopsin in retinal ganglion cells of chickens that functions in the circadian rhythm and pupillary light reflex. Non-mammalian vertebrates have two melanopsins. Mammals have one melanopsin. Early mammals lost one melanopsin, two cone opsins, and extraretinal photoreceoptors, coinciding with a nocturnal phase of mammalian evolution.

Another protein family associated with the eye is the crystallin family, especially found in the lens. Crystallins must exist for a long time in high concentration. These may have evolved from stressor proteins, then to beta crystallins, then to gamma crystallins, which were eye specific, perhaps originally in the retina and finally in the lens (Wistow et al. 2005). Mammals have gamma crystallins A-F. Fish have gamma crystallins M. Gamma N may have had ancestral function in the retina, and later was recruited for the lens. The highly accommodating lenses of birds required a softer structure and incorporated taxon specific crystallins, often coming from enzymes, hence "enzyme crystallins." Gamma N may not be functional in humans or chimps.

The most surprising of the eye related genes are the regulatory genes, including Pax6 and related genes which can initiate eye development in diverse species. In Drosophila seven genes appear to control eye development: eyeless and twin of eyeless are Pax6 homologs sine oculus, eyes absent, dachshund, eye gone, and optix contribute to form a complex network.

Gehring (2005) perhaps gives the strongest case for all eyes evolving from a common ancestral eye. He identified Pax6 as a master control gene for eye development and proposed a new theory about the monophyletic origin of the eyes in evolution. Pax6 can induce ectopic eyes (some place other than the head) in both insects and vertebrates. Not only can Pax genes induce eye formation ectopically on antennae, legs, and wings, but mouse Pax6 causes ectopic eyes in Drosophila. "Because the evolution of a prototypic eye is a highly improbable stochastic event that is not driven by selection, the hypothesis of a polyphyletic origin of the eyes, arising 40 to 65 times independently, is extremely unlikely and incompatible with Darwin's ideas" (Gehring 2005, p. 175). Pax6 related genes have been found in all bilateria analyzed so far, ranging from planarians to humans.

Since echinoderms share deuterstome ancestry with the Phylum Chordata, it is of particular interest to examine the recently decoded genome of the sea urchin (Sea Urchin Genome Sequencing Consortium 2006). The sea urchin has hundreds of genes homologous to mammalian sensory genes, including eye genes. Photoreceptor genes apparently are expressed in the tube feet. Does a sea urchin really need hundreds of sensory genes with no eyes, ears, or nose? Perhaps the deuterstome ancestor evolved eye genes without eyes, or possibly it had eyes and lost them, and these genes were retained for a different use in the sea urchin. Or perhaps the developmental genes evolved even before the protostome-deuterstome split at least 750 million years ago, such that the sea urchin shared a common pool of genes common to animals. These genes, sometimes, in a certain balance, developed eyes while, at other times, were used in developing unrelated structures. Kozmik et al. (2007) reported nine Pax genes in amphioxus, also lacking eyes, including four newly described homologues of six and eyes absent.

Brodbeck and Englert (2004) reported that the mouse has nine Pax genes. Many of these same genes are used in development of mammalian kidney. Thus these regulatory genes exhibit pleiotropy, being expressed in many different tissues. Compared to Gehring (2005), they have suggested a different view of master control genes and hierarchies, and prefer the concepts of circuits and networks instead. "Evolution is conservative, since components of networks . are redeployed in different species and in the development of different organs. At the same time evolution is exploratory and will not use the identical module again but try different combinations of factors, build in additional feedback loops, involve additional components, and abandon others" (Brodbeck and Englert 2004, p. 253).

Could it be that the ancestor of the deuterostomes was a bottom-feeding dweller in the dark? Perhaps many genes accumulated for other sensory functions, as noted in the sea urchin, and then when the first shallow water chordate evolved, these genes were re-wired as photoreceptors and, using the ancient eye-organizing gene, evolved into a camera-type eye. It might have been similar to the hagfish to begin with, which feeds near the bottom and has rudimentary eyes. Eyes that evolved in the dark might also be expected to have a reflective layer behind the retina, as nocturnal animals have today, and hence the photoreceptors being at the back of the retina to receive the reflected light was not such a poor design after all. The total light path would be less obstructed by ganglion cells if the light goes through the ganglion layer once, then to the photoreceptors, some passing on to the reflective layer, and then, without further interference, back to the photoreceptors. Mammals probably evolved in nocturnal niches while dinosaurs dominated the daytime. Could mammals have evolved without the retina rearmost design? Photoreceptors inside the ganglion layer would receive reflected light after it passed twice through the ganglion layer and hence be less effective.

Much research has gone into satisfying Darwin's anxiety about the complexity of the eye. The evidence from both extant and extinct species gives a plausible series of steps for the evolution of camera-type and compound eyes. Do eyes demonstrate gradual evolution? One still has to wonder why even the earliest animals had genes capable of forming eyes and why the visually challenged sea urchin is loaded with hundreds of genes homologous to those expressed in vertebrate eyes. This paradox has emerged as an important theme in the field of evolutionary development (Yoon 2007), so that complex new forms do not require many new mutations or many new genes but instead small changes to existing genes and developmental plans, a sort of "tool kit." Major events in evolution may not depend on new genes or the appearance of new body parts, but the right ecological situation to allow a new expression of genes already present. Conway Morris (2003b, p. 166) calls this inherency, whereby the same basic building blocks of complex structures are available before being recruited for new and more sophisticated tasks so that "emergence relies more on co-option and redeployment than invention." So do the "eyes" have it on the question of evolution? Surely on the anatomical level, Darwin has been vindicated, but on the cellular level many questions remain and proponents of Intelligent Design can be expected to still say nay.

Perhaps the ancestral animal had thousands of genes, all existing in a delicate balance and carrying immense potential. In one daughter lineage, gene duplication and selection achieved a new balance to develop a complex organ like an eye out of that inherent potential. In another daughter lineage, some other set of circumstances at a different time or several times, also allowed that potential to be expressed as eyes. But perhaps that delicate balance in the ancestral animal that was so early achieved in life's history, but so improbably due to gradual steps, and unlikely to have received its immense potential from chance, was a gift from the Creator of information that was present before the creation of the universe.

Arendt, D., K. Tessmar-Raible, H. Snyman, A. Dorresteijn, and J. Wittbrodt. 2004. Ciliary photoreceptors with a vertebrate-type opsin in an invertebrate brain. Science (5697):869-871. http://search.epnet.com/.

Belie, M. 1996. Darwin's black box: The biochemical challenge to evolution. The Free Press, New York. 319 pages.

Bellingham, J., S. Chaurasia, Z. Melyan, C. Liu, M. Cameron, E. Tarttelin, P. Iuvone, M. Hankins, G. Tosini, and R. Lucas. 2006. Evolution of melanopsin photoreceptors: discovery and characterization of a new melanopsin in nonmammalian vertebrates. PLOSBiology 4 (8):e254. http://www.plosbiology.org/.

Brodbeck, S. and C. Englert. 2004. Genetic determination of nephrogenesis: the Pax/Eya/Six gene network. PediatrNephrol19:249-255. http://search.epnet.com/.

Conway Morris, S. 2003a. On the first day, God said . (Review of In the Blink of an Eye by Andrew Parker). American Scientist (July-August):365-367.

Conway Morris, S. 2003b. Life's solution: Inevitable humans in a lonely universe. Cambridge University Press. Cambridge. 485 pages.

Fernald, R. 2006. Casting a genetic light on the evolution of eyes. Science 313 (5795): 1914-1918. http://search.epnet.com/.

Gehring, W. 2005. New perspectives on eye development and the evolution of eyes and photoreceptors. Journal of Heredity 96(3):171-184. http://proquest.umi.com/pdgweb/.

Kozmik, Z., N. Holland, J. Kreslova, D. Oliveri, M. Schubert, K. Jonasova, L. Holland, M. Pestarino, V. Benes, and S. Candiani. 2007. Pax-Six-Eya-Dach network during amphioxus development: conservation in vitro but context specificity in vivo (author abstract). Developmental Biology 306 (1):143-160. http://www.galegroup.com/.

Nilsson, D-E., L. Gislen, M. Coates, C. Skogh, and A. Garm. 2005. Advanced optics in a jellyfish eye. Nature 435:201-205. http://search.epnet.com/.

Oakley, T. and C. Cunningham. 2002. Molecular phylogenetic evidence for the independent evolutionary origin of an arthropod compound eye. Proc Natl Acad Sci USA 99(3):1426-1430. http://www.jstor.org/.

Okano, T., D. Kojima, Y. Fukada, Y. Shichida, and T. Yoshizawa. 1992. Primary structures of chicken cone visual pigments: vertebrate rhodopsins have evolved out of cone visual pigments. Proc Natl Acad Sci USA 89:5932-5936. http://www.jstor.org/.

Parker, A. 2003. In the blink of an eye. Perseus Publishing, Cambridge, MA. 344 pages. Sea Urchin Genome Sequencing Consortium. 2006. The genome of the sea urchin Strongylocentrotus purpuratus. Science 314:941-951.


Conclusion

Despite the high interest in GPCR signaling, its evolution remains enigmatic. There is some evidence that archaeal and bacterial 7TMRs are homologous to eukaryotic 7TM/GPCRs [7]. However, heterotrimeric G proteins/G alpha subunits are only present in eukaryotes. This suggests that ancestral 7TM/GPCRs signaled by mechanisms other than G protein coupling. We found that the arrestin clan is present in archaea and bacteria, raising the possibility that Spo0M could be a primordial 7TMR signaling partner. In addition, our findings of Cnidarian opsins lead us to propose that the ciliary subfamily is ancestral to all bilaterian opsins (also see [34, 35]). That is consistent with Darwin's theory that eyes evolved once.

There were two major arrestin-like gene families in early eukaryotes, arrestin and Vps26. Both protein families are well characterized and point to endocytosis/endosomal dynamics as the ancestral arrestin/Vps26 functions. The duplication of the arrestin domain was a critical event in the creation of ancestral arrestin/Vps26. This could have created autoinhibitory mechanisms (such as those seen in beta arrestins), a recurrent theme in the evolution of signal transduction. The functional similarities of beta arrestins and Vps26 proteins lead us to speculate that the original arrestin/Vps26 was involved in receptor internalization. This could have had two classes of receptor effects in concert: 1) desensitization and recycling/degradation, and 2) signaling. Others have hypothesized that the original role of arrestins may have been as signaling adaptors rather than terminators [67]. Above we mention biochemical evidence that mammalian Vps26 and arrestins could have overlapping roles [47, 48].

The homology of alpha and beta arrestins suggests their molecular functions may be similar. There is evidence from fungi that the alpha arrestin PalF specifically binds an activated 7TMR [28]. That interaction has a positive signaling role that is not yet identified. There are also differences between the alpha and beta classes. Beta arrestins are generally cytoplasmic in unstimulated cells, while alpha arrestins are often associated with membranes [32, 68]. Only visual/betas have helix I in the N domain. And the tails of betas contain clathrin-interacting motifs, while those of alphas have PY motifs. Studies in yeast showed that alpha arrestin PY motifs interact with the WW domains of the HECT E3 ubiquitin ligase Rsp5p. We believe that a major role of alphas is to recruit WW proteins to activated receptors. Alpha and beta arrestins are widely co-expressed. The fact that visual/beta arrestins can hetero-associate [69], hints that alphas and betas may also. Given the near ubiquitious involvement of beta arrestins in 7TMR signaling, we speculate that alphas and betas may function coordinately.


Introduction

Microbial rhodopsins are photoreceptive membrane proteins widely distributed in bacteria, archaea, unicellular eukaryotes, and giant viruses 1,2 . They consist of seven transmembrane (TM) α helices, with a retinal chromophore bound to a conserved lysine residue in the seventh helix (Fig. 1a). The first microbial rhodopsin, bacteriorhodopsin (BR), was discovered in the plasma membrane of the halophilic archaea Halobacterium salinarum (formerly called H. halobium) 3 . BR forms a purple-colored patch in the plasma membrane called purple membrane, which outwardly transports H + using sunlight energy 4 . After the discovery of BR, various types of microbial rhodopsins were reported from diverse microorganisms, and recent progress in genome sequencing techniques has uncovered several thousand microbial rhodopsin genes 1,5,6,7 . These microbial rhodopsins show various types of biological functions upon light absorption, leading to all-trans-to-13-cis retinal isomerization. Among them, ion transporters, including light-driven ion pumps and light-gated ion channels, are the most ubiquitous (Fig. 1b). Ion-transporting rhodopsins can transport several types of cations and anions, including H + , Na + , K + , halides (Cl – , Br – , I – ), NO3 – , and SO4 2 , 8,9,10 . The molecular mechanisms of ion-transporting rhodopsins have been detailed in numerous biophysical, structural, and theoretical studies 1,2 .

a Schematic structure of microbial rhodopsins. b Phylogenic tree of microbial rhodopsins. The subfamilies of light-driven ion-pump rhodopsins targeted in this study are differently colored non-ion-pump microbial rhodopsins and ion-pumping microbial rhodopsins from eukaryotic and giant viral origins are shown in gray.

In recent years, many ion-transporting rhodopsins have been used as molecular tools in optogenetics to control the activity of animal neurons optically in vivo by heterologous expression 11 , and optogenetics has revealed various new insights regarding the neural network relevant to memory, movement, and emotional behavior 12,13,14,15 . However, strong light scattering by biological tissues and the cellular toxicity of shorter wavelength light make precise optical control difficult. To circumvent this difficulty, new molecular optogenetics tools based on red-shifted rhodopsins, which can be controlled by weak scattering and low toxicity longer-wavelength light are urgently needed. Therefore, many approaches to obtain red-shifted rhodopsins have been reported, including gene screening, amino acid mutation based on biophysical and structural insights, and the introduction of retinal analogs 16,17,18 . The insights obtained in these experimental studies, and further theoretical and computational studies 19,20,21,22 revealed basic physical principle regulating absorption maximum wavelengths (λmax) of rhodopsins (also called spectral or color-tuning rule) in which the distortion of retinal polyene chain induced by steric interactions with surrounding residues, electrostatic interaction between protonated retinal Schiff base and counterion(s), and polarizability of the retinal binding pocket play essential role 23 . The λmax of several rhodopsins could be red-shifted by 20–40 nm without impairing the ion-transport function based on these physicochemical insights 17,24,25 . These are successful examples of knowledge-driven experimental approach. Recently, a new method using a chimeric rhodopsin vector and functional assay was reported to screen the λmax and proton transport activities of several microbial rhodopsins that are present in specific environments 26 . This method identified partial sequences of red-shifted yellow (560–570 nm)-absorbing proteorhodopsin (PR), the most abundant outward H + -pumping bacterial rhodopsin subfamily, from the marine environment. These works identified several red-shifted rhodopsins 15,16,18,27 . Especially, most successful optogenetic tools are red-shifted channel rhodopsins such as Chrimson 27,28 and RubyACR 29 which can induce and inhibit neural firing by absorbing 590 and 610-nm light, respectively. The rational amino acid mutation based on the structural insight further red-shifted the λmax of Chrimson to 608 nm 27 . The development of next-generation sequencing technology is expected to continue to more rapidly identify a large number of new rhodopsin genes, including proteins with even longer wavelength-shifted absorption. However, screening of all of them either by experimental or theoretical methods would be very costly. Therefore, a less expensive and more efficient approach to screen red-shifted rhodopsins is needed, and data-driven study is expected as the third class of approach to investigate the color-tuning rule of rhodopsins at low cost.

To estimate the λmax of rhodopsins, we recently introduced a data-driven approach 30 . In this previous study, we investigated the statistical relationship between the amino acid types at each position of the seven TM helices and the absorption wavelength of rhodopsins. We constructed a database containing 796 wild-type (WT) rhodopsins and their variants, the λmax of which had been reported in earlier studies. Then, we evaluated the strength of the relationship with a data-splitting approach, i.e., the data set was divided into a training set and a test set the former was used to construct the predictive model, and the latter was used to estimate the predictive ability. The results of this “proof-of-concept’’ study suggested that the λmax of an unknown family of rhodopsins could be predicted with an average error of ±7.8 nm, which is comparable to the mean absolute error of λmax estimated by the hybrid quantum mechanics/molecular mechanics (QM/MM) 21 method. Considering the computational cost of both approaches, the data-driven approach was found to be much more efficient than the QM/MM approach, while the latter provides insights on the physical origin controlling λmax.

Encouraged by this result, in this study, we introduced a machine-learning (ML)-based experimental design method which enables us screening more efficiently the candidates of rhodopsins that are likely to have red-shift gains with data-driven assist compared to the random or knowledge-driven screening. For this aim, we constructed a new dataset of 3022 wild-type putative ion-pump rhodopsins which were collected from public gene databases (NCBI non-redundant protein sequences, and metagenomic proteins 31 and the Tara Oceans microbiome and virome database 32 ) and for which λmax have not been experimentally investigated yet to explore new red-shifted rhodopsins. The goal of the present study was to identify rhodopsins with λmax longer than the wavelengths of the representative rhodopsins in each subfamily of microbial rhodopsins for which the λmax has already been reported (base wavelengths). Here, we call the degrees of red-shift of the wavelength from the base wavelength the “red-shift gain”. We focus on rhodopsins with large red-shift gains because this would lead to the identification of amino acid types and residue positions that play important roles in red-shifting absorption wavelengths. Also, it is practically important in optogenetics applications to have a wide variety of ion-pumping rhodopsins from each subfamily to construct a new basis for rhodopsin toolboxes with red-shifted absorption and various types of ion species that can be transported. We constructed the ML-based experimental design method so that it could properly predict the expected red-shift gains, and applied this new method to 3022 putative ion-pumping rhodopsins derived from archaeal and bacterial origins that can be easily expressed in Escherichia coli (Fig. 1b).

We conducted experiments by introducing the synthesized rhodopsin genes into E. coli to measure the absorption wavelengths of 65 candidates for which the ML-based experimental design method predicted that the expected gains were >10 nm. Of these 65 selected candidates, 39 showed substantial coloring in E. coli cells, 32 showed actual red-shift gains, 6 showed blue-shifts, and 1 showed no change, i.e., 82% (=32/39, 7.025 × 10 −5 ) of the selected candidates showed actual red-shift gains. We then investigated the ion-transportation properties of the rhodopsins for which the red-shift gains were >20 nm, and found that some actually had desirable ion-transporting properties, suggesting that they (and their variants) could potentially be used as new optogenetics tools. Furthermore, the differences in the amino acid sequences of the newly examined rhodopsins and the representative ones in the same subfamily could be used for further investigation of the red-shifting mechanisms. This result suggests that it should be possible to find rhodopsins that have desired properties without conducting exhaustive biological experiments, and suggests that data-driven ML-based approaches should play effective roles in the experimental design of rhodopsin and other photobiological studies.


Abstract

Six rhodopsin mutants containing disulfide cross-links between different cytoplasmic regions were prepared: disulfide bond 1, between Cys65 (interhelical loop I−II) and Cys316 (end of helix VII) disulfide bond 2, between Cys246 (end of helix VI) and Cys312 (end of helix VII) disulfide bond 3, between Cys139 (end of helix III) and Cys248 (end of helix VI) disulfide bond 4, between Cys139 (end of helix III) and Cys250 (end of helix VI) disulfide bond 5, between Cys135 (end of helix III) and Cys250 (end of helix VI) and disulfide bond 6, between Cys245 (end of helix VI) and Cys338 (C-terminus). The effects of local restrictions caused by the cross-links on transducin (GT) activation and phosphorylation by rhodopsin kinase (RK) following illumination were studied. Disulfide bond 1 showed little effect on either GT activation or phosphorylation by RK, suggesting that the relative motion between interhelical loop I−II and helix VII is not crucial for recognition by GT or by RK. In contrast, disulfide bonds 2−5 abolished both GT activation and phosphorylation by RK. Disulfide bond 6 resulted in enhanced GT activation but abolished phosphorylation by RK, suggesting the structure recognized by GT was stabilized in this mutant by cross-linking of the C-terminus to the cytoplasmic end of helix VI. Thus, the consequences of the disulfide cross-links depended on the location of the restriction. In particular, relative motions of helix VI, with respect to both helices III and VII upon light activation, are required for recognition of rhodopsin by both GT and RK. Further, the conformational changes in the cytoplasmic face that are necessary for protein−protein interactions need not be cooperative, and may be segmental.

This work was supported by NIH Grants GM28289 and NEI EY11716 (H.G.K.) and NIH Grant EY05216 and the Jules Stein Professorship Endowment (W.L.H.). J.K.-S. is the recipient of a Howard Hughes Medical Institute Predoctoral Fellowship. J.H. is the recipient of a Howard Hughes Medical Institute Physician Postdoctoral Fellowship.

This is paper 36 in the series “Structure and Function in Rhodopsin”. The preceding paper is by Hwa et al. (1).


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