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Copyright © 2008 American Scientific Publishers All rights reserved Printed in the United States of America Journal of Biomedical Nanotechnology Vol.4,4,44-51, 1–8, 2008 Vol. Functional Control by Codon Bias in Magnetic Bacteria Megha Sharma, Vivek Hasija, Mohit Naresh, and Aditya Mittal∗ Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India Keywords: Magnetic Bacteria, Nanomagnets, Codon Bias, Protein Expression, Nano-Propellers, Flagella, Gene Translation, Codon Evolution. 1. INTRODUCTION Achieving nano-scale control of directed motion for micron-scale bodies is a fascinating concept having a multitude of exciting possibilities in biomedical nanotechnology. Majority of prokaryotes are motile and bacteria are no exception. Motile bacteria have enormous potential to serve as model systems for understanding nano-scale control of motion of micron-scale bodies under different fluid conditions. Bacterial motility is due to presence of flagella (plural of “flagellum”) that work like nanopropellers on the bacterial cell surface. These bacterial nanopropellers are made up of multiple molecular components (proteins) to perform a specific function on the surface of a living cell contributing to its motility. Bacterial flagella are long, thin helical filaments with one end free and other attached to the cell, which rotate like screws and have been studied in detail for the peritrichously flagellated bacteria, especially E. coli. Discovery of magnetotactic bacteria triggered great interest in the possibility of extraterrestrial life.1–3 In more ∗ Author to whom correspondence should be addressed. J. Biomed. Nanotechnol. 2008, Vol. 4, No. 1 recent times, investigations on the ability of these bacteria to manufacture nanomagnets of controlled anisotropies and highly uniform size distributions4 have opened up avenues for fascinating applications including those for biomedical purposes.5 6 Magnetotactic bacteria are equipped with their own nanopropellers (flagella) and nanomagnets that allow them to undergo magneto-aerotaxis.7–9 Magnetotactic bacteria are also highly motile, however, not much is known about the specifics of their nanopropeller systems. While E. coli utilize their nanopropellers for chemotaxis, the magnetotactic bacteria utilize their nanopropellers for magneto-aerotaxis. To understand motility of magnetotactic bacteria (and hence nano-scale control of motion for synthetic micron-scaled bodies by utilizing nano-magnets manufactured by these bacteria), we initiated studies on uncoupling the magnetic component of their motion from the nano-propeller driven motion. Utilizing a simple functional assay with a 33 ms time resolution10 11 we measured the swimming speeds of E. coli (strain JM109) and two strains of magnetotactic bacteria, Magnetospirillum magnetotacticum and Magnetospirillum gryphiswaldense. E. coli was found to swim with speed of 1863±064 m/s (mean ± s.d., n = 3, n refers to independent experiments 1550-7033/2008/4/001/008 doi:10.1166/jbn.2008.001 441 RESEARCH ARTICLE Directed and controlled motion of small (micron sized and smaller) objects in fluid systems is an active area of research in biomedical nanotechnology. Magnetotactic bacteria undergo a kind of directed and control motion called magneto-aerotaxis by utilizing nanopropellers (flagella) and nanomagnets. While studying the role of nanomagnets in magnetic-bacterial motility to investigate nano-scale control of motion, we have serendipitously discovered a major protein specific codon bias residing in the Magnetospirillum magnetotacticum genome. While primary sequences of flagellar, iron uptake and the house-keeping RNA polymerase proteins are identical in magnetic bacteria compared to E. coli and mammalian cells, there is no genetic similarity for flagellar and iron uptake proteins. In contrast, the house-keeping RNA polymerase in magnetic bacteria shows complete genetic similarity also. Surprisingly, the lack of any genetic homology in flagellar and iron uptake proteins, in spite of identical primary amino acid sequences in different organisms, is a consequence of a protein specific codon bias, thereby resulting in non-identical gene sequences. This codon bias is directly correlated with differences in protein functions specific to magnetic bacteria. Based on our findings, we propose a bold “Functional Control by Codon Bias” (FCCB) hypothesis suggesting that protein function is controlled by codons responsible for its primary sequence in addition to the primary sequence itself. The remarkable feature of our proposal is that even if primary sequences of two proteins are identical, utilization of different codons to express those sequences directly affects the function of the proteins. FCCB Hypothesis (a) Sharma et al. (b) (c) (d) (e) (f) RESEARCH ARTICLE Fig. 1. Differences in E. coli and magnetotactic bacteria. (a, b) Morphological differences observed in two bacterial cells with a 100× objective using a glass slide and a cover slip. (c) TEM of a negatively stained sample of a magnetic bacterial cell with nanomagnets aligned inside the cell. The scale bar represents 200 nm. (d) Alignment and connectivity of the nanomagnets is disturbed after lysing the bacterial cells. The scale bar represents 20 nm. (e, f) Cartoon representations comparing the features of E. coli and magnetic bacteria. The magnetic bacterial cells (f), containing nanomagnets, are twice as long as E. coli (e) with the magnetic bacterial flagellum being half the length of that in E. coli. with each experiment measuring 10–40 individual bacterial cells) where as the magnetic bacteria were found to swim with speeds of 32 ± 1030 m/s (n = 4, two experiments for each strain of the magnetic bacteria). A two fold higher speed of magnetic bacteria compared to E. coli was in agreement with separately reported results by other groups.12 13 However, it is interesting to note that while magnetic bacteria (length ∼ 3–4 m11 ) are about twice as long as E. coli (length ∼ 1.5–2 m,11 14 Figs. 1(a, b)), with chains of nano-magnets aligned inside them (Fig. 1(c)) that start losing their connectivity as well as perfect alignment after cell lysis (Fig. 1(d)), they consist of only 1–2 nanopropellers per bacterial cell compared to at least 4 nanopropellers per E. coli cell.12 Moreover, the magnetic bacterial nanopropeller is only 1–4 m long with a diameter of 12–20 nm,13 compared to an E. coli nanopropeller that is 10–20 m long with a diameter of ∼50 nm.12 The differences in length of a bacterial cell and its flagellum, for E. coli and magnetic bacteria, are depicted in Figures 1(e), (f), respectively. It is also interesting to note that Pseudomonas aeruginosa, which has a single flagellum (like magnetic bacteria), but with dimensions similar to E. coli, swims at speeds similar to E. coli.15 16 These observations raise a very interesting question. How do magnetic bacteria move with speeds twice as fast as compared to other bacteria with at least half the number of nanopropellers, each nanopropeller being significantly smaller than other motile bacteria? To answer the above, in absence of crystal structures of magnetic bacterial nanopropellers, we decided to 2 45 investigate protein sequences of the individual components of the nanopropellers. We report very surprising findings that identical protein primary sequences, but with no genetic homology, result in different functionality in different systems. In contrast, a house-keeping protein like RNA polymerase, with identical protein primary sequence as well as genetic homology, has the same functionality regardless of the system. 2. MATERIALS AND METHODS 2.1. Chemicals All reagents purchased from commercial sources were used as received. Vitamin solution and trace element solution were prepared afresh. Vitamin solution components: biotin, folic acid, pyridoxine-hydrochloride, thiaminehydrochloride dihydrate, riboflavin, nicotinic acid, D-calcium-pantothenate, and Vitamin B12 were obtained from Himedia. For trace element solution, nitrilotriacetate acid, cobalt sulfate heptahydrate (CoSO4 × 7H2 O), and disodium molybdate dihydrate (Na2 MoO4 × 2H2 O) were obtained from Qualigen; Magnesium sulfate heptahydrate (MgSO4 × 7H2 O), manganese sulfate heptahydrate (MnSO4 × 7H2 O), sodium chloride (NaCl), ferrous sulfate heptahydrate (FeSO4 × 7H2 O), calcium sulfate heptahydrate (CaSO4 ×7H2 O), zinc sulfate heptahydrate (ZnSO4 × 7H2 O), copper sulfate pentahydrate (CuSO4 × 5H2 O), potassium aluminium sulfate dodecahydrate (KAl(SO4 2 × 12H2 O), boric acid (H3 BO3 ), nickel chloride hexahydrate (NiCl2 × 6H2 O), and sodium selenite pentahydrate J. Biomed. Nanotechnol. 4, 4,44-51, 1–8, 2008 FCCB Hypothesis Sharma et al. (Na2 SeO3 × 5H2 O) were purchased from Merck. For media 380 and 512, resazurin, sodium thioglycolate, and yeast extract were obtained from Himedia; Monobasic potassium phosphate (KH2 PO4 ), sodium nitrate (NaNO3 ), L(+)-Tartaric acid, succinic acid, agar (for semi-solid media), dibasic potassium phosphate (K2 HPO4 ), and ammonium chloride (NH4 Cl) were obtained from Merck; Ferric citrate was purchased from Lobachemie. For ferric quinate solution, ferric chloride hexahydrate (FeCl3 × 6H2 O) and quinic acid were purchased from Merck and Spectrochem (India) respectively. Distilled water was used for all solutions. 2.2. Growth Media 2.3. Inoculation The bacteria were grown in 250 ml flasks, with custom made rubber caps, and 30 ml anoxic vials, with screw caps and air tight rubber lining. 10 ml of inoculum was added to 150 ml media in 250 ml flasks and 1 ml inoculum was added to 10 ml media in 30 ml vials. Inoculum was added with a hypodermic syringe through the rubber cap taking care not to introduce air. The bacteria were allowed J. Biomed. Nanotechnol. 4, 4,44-51, 1–8, 2008 2.4. Video Microscopy and Speed Measurements 1 ml of sample was withdrawn for video microscopy. The cells were observed by placing a drop of sample on a flat slide and observing under oil immersion at 100× magnification. 10 seconds videos were captured at a 33 frames/ms resolution.10 17 For analysis, 300 frames, 33 ms apart, were extracted from each 10 s videos. Using Scion Image software, the average speed was measured. The average speed was measured by measuring the distance between the positions of the bacteria between two successive frames and dividing with the time (33 ms). The overall speed was defined in terms of the total distance covered by the bacteria divided by the total time. For Magnetospirillum magnetotacticum, 5–7 bacteria were observed and for Magnetospirillum gryphiswaldense, 30–40 bacteria were observed.10 17 2.5. Protein Similarity and Codon Specificity Analysis Protein and nucleotide sequences of known mammalian iron regulatory proteins18–20 and flagellar proteins12 were obtained from NCBI. The genome blast tool (http://www.ncbi.nlm.nih.gov/sutils/genom_table.cgi) was then used to search for these proteins in Magnetospirillum magnetotacticum MS-1. While comparing nucleotide sequences, the default option of Mega BLAST was unselected. This is because Mega BLAST uses the greedy algorithm for nucleotide sequence alignment search. This program is optimized for aligning sequences that differ slightly as a result of sequencing or other similar errors. As a result if nucleotide sequences were compared using mega BLAST “no match” was obtained for any of the proteins. Sequences with e-value less than 10−5 were considered to be a match. To determine codon specificity, protein translation-table number 11 from NCBI was used. For each protein the nucleotide and protein sequences were compared for both the query and M. magnetotacticum. The number of times a particular codon was used to code for an amino acid was counted using MATLAB (Mathworks Inc., USA). This was done for both iron regulatory and flagellar proteins. 3. RESULTS We searched for the flagellar proteins of E. coli12 in the recently reported genome for the magnetotactic bacteria M. magnetotacticum (being sequenced at the Joint Genome Institute) using BLAST. This strain was specifically chosen since our experimental work is being carried out with this 463 RESEARCH ARTICLE Media 380 and 512, as per DSMZ (Germany) nomenclature, were used for Magnetospirillum magnetotacticum and Magnetospirillum gryphiswaldense, respectively. The media were prepared following standard protocol provided by DSMZ. Medium 380, used for cultivation of M. magnetotacticum contained (per liter): 10 ml vitamin solution, 5 ml trace elements, 2 ml Fe(III) quinate solution, 0.5 mg resazurin, 0.68 g KH2 PO4 , 0.12 g NaNO3 , 0.05 g Nathioglycolate, 0.37 g L(+)-Tartaric acid, 0.37 g succinic acid, and 0.05 g Na-acetate. All the ingredients, except Na-thioglycolate, were mixed and the medium was boiled for 3 mins, after adjusting pH to 6.5 with NaOH. The medium was autoclaved at 121 C for 15 mins. 0.01 M Fe(III) quinate solution was prepared by dissolving 0.45 g FeCl3 × 6H2 O and 0.19 g quinic acid in 100 ml distilled water. This solution was autoclaved separately and added to remaining autoclaved media components. TES and vitamin solution were filter sterilized and added to autoclaved media. For cultivation of M. gryphiswaldense, medium 512 contained (per liter): 0.5 g KH2 PO4 , 1 g Na-acetate, 0.1 g NH4 Cl, 0.1 g yeast extract, 20 m Fe(III) citrate, and 0.5 g Na-thioglycolate. The pH was adjusted to 6.8 and the medium was prepared 2–3 days before use. For both media freshly prepared Na-thioglycolate was filter sterilized and added just before inoculation. The media was dispensed in anoxic vials with screw caps. Anoxic conditions were maintained by purging nitrogen for 15 minutes. Sterile air was added with a hypodermic syringe through the rubber cap to a concentration of 1% (v/v) in the vial. To prepare semi-solid medium, agar was added to a concentration of 1.3 g/1000 ml media (only for medium 380). to grow at 30 C for 2 weeks and growth was monitored by carefully withdrawing small samples with a hypodermic needle and observing under a microscope. Quantitative assessment of bacterial growth was not done as a part of this study, since it was not required for the purpose of the work done here. FCCB Hypothesis Sharma et al. strain. We found homologous proteins, corresponding to various components of the E. coli nanopropeller assembly in the magnetic bacterial genome (Table I). The extremely small e-values (e 10−5 ) obtained for most proteins, using BLAST, indicated nearly exact protein primary sequences for the nanopropeller components in both the bacteria. However, very interestingly, no match was found when the nucleotide sequences were compared (e 10−5 ) for the two bacteria (Table I). Was the astounding lack of any homology in the nucleotide sequences of a single nanopropeller component proteins between E. coli and magnetic bacteria a general feature of the latter or does the magnetic bacteria have an altogether different nucleotide coding arrangement, which still results in the same primary sequence assembly? To answer the above question, we searched for a “house keeping” protein of gram negative bacteria (both the bacteria studied by us are gram negative) called RNA polymerase. While the protein sequences, for different subunits of RNA polymerase, present in E. coli and the magnetic bacterial genome were expectedly identical, surprisingly there was very significant homology (in contrast to a complete lack of homology for flagellar proteins) on the nucleotide level also for the subunits (e 10−5 ). These results, shown in Table I, led us to further ask whether RESEARCH ARTICLE Table I. Blast searches for various proteins in the M. magnetotacticum genome. Protein Flagellar proteins IRPs RNA polymerase Protein/ Subunit Accession number Protein e-value NT e-value FlgB FlgC FlgD FlgE FlgF FlgG FlgH FlgI FlgK FlhA FlhB FliA FliC FliF FliG FliI FliM FliN FliP FliR IRP1/Aconitase IRP2 subunit subunit subunit subunit BAB34874.1 P0ABX2 YP_852174.1 BAA35885.2 BAA35886.1 BAB34879.1 BAB34880.1 BAB34881.1 BAB34883.1 BAB33679.1 BAB36013.1 BAB36084.1 ABI23966.1 BAB36100.1 BAB36101.1 BAB36103.1 BAB36107.1 BAB36108.1 BAA15773.1 BAB36112.1 NP_002188.1 CAB62825.1 BAE77333.1 AAC76962.1 AP_004495.1 AAA24601.1 6 × 10−09 9 × 10−21 2 × 10−20 3 × 10−20 4 × 10−19 1 × 10−66 3 × 10−18 3 × 10−63 4 × 10−17 1 × 10−81 8 × 10−56 7 × 10−15 8 × 10−08 4 × 10−53 2 × 10−36 6 × 10−97 1 × 10−24 2 × 10−15 1 × 10−59 2 × 10−11 6 × 10−86 1 × 10−23 2 × 10−158 0 3 × 10−83 8 × 10−120 7 × 10−07 18 02 14 001 006 02 032 049 1 × 10−07 002 001 17 049 007 041 0005 012 085 091 10 62 7 × 10−36 3 × 10−41 n.d.∗ 1 × 10−66 e-values obtained are given for both the protein as well as corresponding nucleotide matching. ∗ Nucleotide sequence for this protein was not found and hence not compared. 47 4 presence of identical primary sequences of proteins in absence of any nucleotide level homology was a function specific feature in magnetic bacteria. Thus, we carried out similar blast searches for Iron Regulatory Proteins (IRPs: IRP1 and IRP2) from mammalian18–20 as well as bacterial sources (in bacteria, IRP1 is called aconitase) in the magnetic bacterial genome. The logic behind these searches was that if IRPs are present in magnetic bacteria, then one would expect primary sequences of these proteins to be identical to the other sources, since iron transport is key to nanomagnet assembly inside magnetic bacteria. However, based on the nucleotide dependent functional differences found in flagellar proteins, we would also expect no nucleotide similarity for IRPs from other sources in the magnetic bacterial genome. This is so since IRPs in magnetic bacteria are clearly expected to play a role in iron transport towards nanomagnet formation, a functional feature absent in other sources. Once again, to our pleasant surprise, we found that primary sequences of IRPs identical to those found in mammalian systems are present in the magnetic bacterial genome however there is no nucleotide homology (Table I, e 10−5 ). Thus, we had clearly found a nucleotide level control of function of proteins in magnetic bacteria. On one hand, the magnetic bacterial nanopropellers providing unique motility characteristics and iron regulatory proteins providing their unique roles in iron transport leading to nanomagnet production inside magnetic bacteria had no nucleotide matches from other sources in spite of identical protein primary sequences. On the other hand, RNA polymerase, which has exactly the same functional outputs in magnetic bacteria compared to E. coli had identical protein primary sequences as well as nucleotide sequences in both the systems. This, to our knowledge, is the first time that a correlation has been found between functional differences of identical proteins (i.e., identical primary sequences) differing on the nucleotide level. What was the reason for these nucleotide dissimilarities, in spite of the same primary sequence, that were correlating well with different protein functions? To investigate this, we studied the codon preferences utilized in magnetic bacteria and the other sources for the proteins shown in Table I. Soon it became apparent that magnetic bacteria had a particular codon bias for amino acid residues. Except for methionine and tryptophan, that have only one codon for each of them, we compared the codons for all the other 18 amino acid residues (which have 2–6 codons for each residue). Close inspection revealed a certain bias, in magnetic bacteria, against utilizing “T” or “A” as the third base in the codons for these 18 residues. These results are more clearly shown in Figure 2. It can be seen from Figure 2(a), that when we consider the percentage of times “non T or A” in the third base of codons are plotted as a function of different proteins, the magnetic bacteria (gray bars) appear to have a higher percentage in all cases. Were J. Biomed. Nanotechnol. 4, 4,44-51, 1–8, 2008 FCCB Hypothesis Sharma et al. 140 (a) 120 Percentage 100 80 60 40 20 σ β’ β IRP-2 IRP-1 FliR FliP FliN FliM FliI FliG FliF FlhB FlhA FlgK FlgL FlgE FlgD FlgC FlgB 0 0 –2 Log(p) –4 –6 –8 –10 (b) –12 these higher percentages statistically relevant? To check this, we carried out t-tests between the non T or A codon percentages for the 18 amino acids for magnetic bacteria as well as the other sources. Figure 2(b) shows the log of “p” values obtained from those t-tests. The dashed line shows p = 001. Any p value smaller than this (i.e., more negative in Fig. 2(b)) signifies statistically relevant difference in the codon usage while avoiding T or A as the third base in the codons. Clearly, while the RNA polymerase subunits do not show any statistically relevant differences in codon preferences (all the three bars in Fig. 2(b) are greater than p = 001), most of the flagellar (11 out of 15) proteins and both the iron regulatory proteins show substantial statistical differences. Therefore, the next question was where specifically was this codon preference arising from? Grouping amino acid residues based on conventional systems (e.g., polar: neutral, negatively and positively charged or non-polar) did not yield any specific insight. However, when we divided the amino acid residues into two groups based on the number of codons for each residue, very interesting J. Biomed. Nanotechnol. 4, 4,44-51, 1–8, 2008 results were observed. Figures 3(a and c) show groups of amino acids having more than two codons for each amino acid (Fig. 3(a)) and groups of amino acids having only two codons (Fig. 3(c)). For ease of visualization, Figure 3 shows results for all combined subunits of individual proteins. For example, all the 15 flagellar subunits shown in Table I and Figure 2 are taken together as flagellar proteins. Thus, if 10 amino acid residues have more than two codons for each residue, the appearance of these 10 amino acids is evaluated for all 15 flagellar proteins, and hence n = 150 for the pair of bars representing flagellar proteins in Figure 3(a). It is clear from Figures 3(a and b) that magnetic bacteria (gray bars) have a significantly higher percentage of non T or A as the third base in codons compared to other sources (p 001), regardless of proteins. However, this result is in contrast to results in Table I and Figure 2, where it is clear RNA polymerase has nucleotide identity and similar codon usage in magnetic bacteria and other sources. This is easily explained by considering the relative low frequency of these amino acid residues in the protein sequences, along with the results 48 5 RESEARCH ARTICLE Fig. 2. Codon bias in magnetic bacteria. (a) Percentage of codons not containing T or A as the third base for all the amino acid residues in particular proteins for E. coli (open bars) and magnetic bacteria (gray bars). Since methionine and tryptophan have only one codon, they were not included in the comparisons. Thus, for each data set, n = 18. First a protein was found in the magnetic bacterial genome using BLAST. Then, occurrence of each amino acid residue in a particular protein sequence was counted. Then codons for each of the amino acid residues were tabulated. Subsequently, the percentage of codons with no T or A the third base was calculated for each amino acid. Finally, percentages of the 18 amino acids were pooled to calculate the mean ± standard deviation of the percentage of codons without T or A in the third base. (b) log of p-values from t-tests performed on data represented by each set of bars (i.e., open and gray) in (a). The dashed line corresponds to a p-value of 0.01. Any black bar below it (i.e., more negative) shows a significant difference in the open and gray bars in (a) and any black bar above the dashed line shows no statistical difference. All marked in yellow constitute the flagella, orange constitute the IRPs and blue constitute RNA polymerase. FCCB Hypothesis Sharma et al. 120 120 Percentage (a) (c) 100 100 80 80 60 60 40 40 20 20 0 0 Flagellar IRPs RNA Pol 0 RNA Pol –4 –10 –6 –15 –8 – 20 –10 – 25 –12 (b) – 30 RESEARCH ARTICLE IRPs –2 –5 Log(p) Flagellar 0 (d) –14 Fig. 3. Codon bias in magnetic bacteria, absent/minimal in a housekeeping protein like RNA polymerase, specifically arises from residues for which there exist only two codons. (a, c) Percentage of codons not containing T or A as the third base for all the amino acid residues having more than two codons (a), or two codons only (c), in particular proteins for E. coli (open bars) and magnetic bacteria (gray bars). Note that all the flagellar proteins in Figure 2(a) and Table I (i.e., total 15) were pooled into one category called flagellar, both the IRPs were pooled as one and all the RNA polymerase subunits were pooled into RNA pol. Once again, methionine and tryptophan have only one codon, so they were not included in the comparisons. Thus, in (a) n = 150 for flagellar proteins (15 flagellar proteins, 10 residues having more than two codons), n = 20 for IRPs (2 IRPs), n = 30 for RNA polymerase (3 subunits). Similarly in (c) n = 120 for flagellar (15 flagellar proteins, 8 residues having two codons), n = 16 for IRPs, n = 24 for RNA polymerase. All data in (a) and (c) is mean ± standard deviation. (b, d) The log of p-values obtained for t-tests performed on the data shown in (a) and (c) respectively. Note that the Y -axis scale is different in (b) and (d). While the RNA polymerase as the largest p-values in both the figures, using a statistically significance criteria of p = 001 (dashed lines), there is no significant differences in the open and gray bars for RNA polymerase in (c) only as shown by the corresponding black bar in (d). shown in Figure 3(d). While the usage of non T or A codons in flagellar as well as iron regulatory proteins, for residues having only two codons corresponding to each of them, is significantly higher in magnetic bacteria compared to other sources (Fig. 3(d), p 001), there is no difference between codon preferences for magnetic bacteria and other sources for RNA polymerase. Thus, it is clear that when there is only a 50% chance of choosing T or A as the third base in codons (out of two possible codons, one has either T or A in the third base), somehow the magnetic bacteria have evolved a bias against using these codons. 4. DISCUSSION AND CONCLUSIONS We report functional dependence of proteins with identical primary sequences on usage of specific codons utilized for expressing those primary sequences in magnetic bacteria. Here it is pertinent to mention that codon bias has already been actively implicated in misfolding of proteins, 6 49 especially with attempts to over-express certain external proteins in bacterial systems using plasmids.21–24 However, the prime reason attributed to this misfolding has been considered as overloading of the natural bacterial protein expression machinery due to plasmids. How can nucleotide sequences affect protein function with identical primary sequences? We propose a novel “Functional Control by Codon Bias” (FCCB) hypothesis as a potential answer to this question. While our newly proposed (FCCB) hypothesis is sure to be quite controversial since at this stage it is purely theoretical and challenges the well accepted norm that only primary sequences, leading to particular protein structures under given conditions, control protein functionality, it indeed is bound to open up new experimental avenues. Figure 4 shows a cartoon representation of our FCCB hypothesis. For convenience, we have utilized a cartoon of the bacterial nanopropeller (flagellar protein) with its major molecular components to conceptualize the FCCB hypothesis. It is J. Biomed. Nanotechnol. 4, 4,44-51, 1–8, 2008 FCCB Hypothesis Sharma et al. ? Fig. 4. Functional control by codon bias (FCCB) hypothesis. Assembly of bacterial nanopropellers (flagellar) is shown as an example. The assembly results from transcription and translation of genetic codes using the same machinery (shown in red). However, subtle differences in the finally assembled protein structure (shown by arrows in the lower flagellar protein) can results from different genetic coding (due to codon bias) leading to different kinetics of transcription/translation and hence assembly of the complex. This could lead to different protein functionality in spite of the same primary sequences of amino acids. J. Biomed. Nanotechnol. 4, 4,44-51, 1–8, 2008 Acknowledgments: This work was supported by funding from SERC, Department of Science and Technology, Government of India, awarded to Aditya Mittal. Megha Sharma and Mohit Naresh acknowledge support from the Department of Biochemical Engineering and Biotechnology IIT Delhi. References and Notes 1. D. S. McKay, E. K. Gibson, Jr., K. L. Thomas-Keprta, H. Vali, C. S. Romanek, S. J. Clemett, X. D. Chillier, C. R. Maechling, and R. N. Zare, Search for past life on mars: Possible relic biogenic activity in martian meteorite ALH84001. Science 273, 924 (1996). 2. E. I. Friedmann, J. Wierzchos, C. Ascaso, and M. Winklhofer, Chains of magnetite crystals in the meteorite ALH84001: Evidence of biological origin. Proc. Natl. Acad. Sci. USA 98, 2176 (2001). 3. K. L. Thomas-Keprta, S. J. Clemett, D. A. Bazylinski, J. L. Kirschvink, D. S. McKay, S. J. Wentworth, H. Vali, E. K. Gibson, Jr., M. F. McKay, and C. S. Romanek, Truncated hexa-octahedral magnetite crystals in ALH84001: Presumptive biosignatures. Proc. Natl. Acad. Sci. USA 98, 2164 (2001). 4. D. A. Bazylinski and R. B. Frankel, Magnetosome formation in prokaryotes. Nat. Rev. Microbiol. 2, 217 (2004). 5. K. J. Kirk, Nanomagnets for sensors and data storage. Contemporary Phys. 40, 61 (2000). 6. C. Alexiou, R. Jurgons, C. Seliger, and H. Iro, Medical applications of magnetic nanoparticles. J. Nanosci. Nanotechnol. 6, 2762 (2006). 7. R. P. Blakemore, Magnetotactic bacteria. Science 190, 377 (1975). 8. D. L. Balkwill, D. Maratea, and R. P. Blakemore, Ultrastructure of a magnetic spirillum. J. Bacteriol. 141, 1399 (1980). 9. D. A. Bazylinski, Structure and function of the bacterial magnetosome. ASM News 61, 337 (1995). 10. R. Gupta, M. Sharma, and A. Mittal, Effects of membrane tension on nanopropeller driven bacterial motion. J. Nanosci. Nanotechnol. 6, 3854 (2006). 11. M. Sharma, M. Naresh, and A. Mittal, Morphological changes in magnetotactic bacteria in presence of magnetic fields. J. Biomed. Nanotechnol. 3, 75 (2007). 12. H. C. Berg, The rotary motor of bacterial flagella. Annu. Rev. Biochem. 72, 19 (2003). 13. K. T. Silva, F. Abreu, F. P. Almeida, C. N. Keim, M. Farina, and U. Lins, Flagellar apparatus of south-seeking many-celled magnetotactic prokaryotes. Microsc. Res. Tech. 70, 10 (2006). 14. J. Miao, K. O. Hodgson, T. Ishikawa, C. A. Larabell, M. A. LeGros, and Y. Nishino, Imaging whole Escherichia coli bacteria by using single-particle X-ray diffraction. Proc. Natl. Acad. Sci. USA 100, 110 (2003). 50 7 RESEARCH ARTICLE possible that while the machinery for transcription and translation is identical for magnetic bacteria and other species (e.g., RNA polymerase), shown in red in Figure 4, if the nucleotide sequences to be transcribed or translated are different, then there would be completely different kinetics of expression and folding of these primary sequences. This would lead to changes in the eventual protein structures, presumably subtle but significant enough (shown by arrows in the lower flagellar structure) to cause functional differences for those proteins. These changes would be even more prominent for functional multi-protein complexes, where kinetics and/or the order of assembling several protein subunits would produce changes in the final functional protein complex structure and function. Interestingly, the nucleotide level correlation with protein function in our study comes from a codon bias arising from amino acid residues which have only two codon options, one having T or A as the third base and the other without T or A as the third base, where there is a 50% chance of choosing one codon over the other. Assembly of a different nanopropeller system due to codon bias might lead to the uniqueness of magnetic bacteria that are motile with speeds twice as fast as compared to other bacteria with half the number of nanopropellers, each nanopropeller being significantly smaller than other motile bacteria. Further, FCCB hypothesis may be a key link to understanding why homologous iron uptake and transport proteins serve different roles in magnetotactic bacteria and other bacteria or mammalian cells. Our FCCB hypothesis has the potential to invoke a new debate, if not a significant paradigm shift, in evolutionary biology. While codon bias has been reported for several different species from microbial to higher systems, we suggest altogether a new impact resulting out of the codon bias. We propose that codon bias has its amplified effects only on proteins whose functions are specific to a particular species and not on housekeeping proteins. Finally, our results and the FCCB hypothesis clearly have profound implications in general (i.e., not just magnetic bacteria) in the post-genomic era especially for utilizing recombinant strains for expressing foreign genetic codes (e.g., for biological production of nano-materials), and also in the field of protein function predictions. FCCB Hypothesis Sharma et al. 15. C. M. Toutain, M. E. Zegans, and G. A. O’Toole, Evidence for two flagellar stators and their role in the motility of Pseudomonas aeruginosa. J. Bacteriol. 187, 771 (2005). 16. A. Touhami, M. H. Jericho, J. M. Boyd, and T. J. Beveridge, Nanoscale characterization and determination of adhesion forces of Pseudomonas aeruginosa pili by using atomic force microscopy. J. Bacteriol. 188, 370 (2006). 17. S. Arora, V. Bhat, and A. Mittal, Correlating single cell motility with population growth dynamics for flagellated bacteria. Biotechnol. Bioeng. 97, 1644 (2007). 18. E. C. Theil and R. S. 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Rahbe, Codon usage bias and tRNA over-expression in Buchnera aphidicola after aromatic amino acid nutritional stress on its host Acyrthosiphon pisum. Nucleic Acids Res. 34, 4583 (2006). 23. I. Henry and P. M. Sharp, Predicting gene expression level from codon usage bias. Mol. Biol. Evol. 24, 10 (2007). 24. P. Lu, C. Vogel, R. Wang, X. Yao, and E. M. Marcotte, Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nat. Biotechnol. 25, 117 (2007). RESEARCH ARTICLE Received: 29 September 2007. Revised/Accepted: 8 October 2007. 51 8 J. Biomed. Nanotechnol. 4, 4,44-51, 1–8, 2008 J. Biomed. Nanotechnol. 4, 44-51, 2008 Graphical Abstract Functional Control by Codon Bias in Magnetic Bacteria Megha Sharma, Vivek Hasija, Mohit Naresh, Aditya Mittal ? In this study, we propose a bold “Functional Control by Codon Bias” (FCCB) hypothesis suggesting that protein function is controlled by codons responsible for its primary sequence in addition to the primary sequence itself. The remarkable feature of our proposal is that even if primary sequences of two proteins are identical, utilization of different codons to express those sequences directly affects the function of the proteins.