The work was jointly supported by the National Natural Science Foundation of China (grant no. 21676026), the National Key R&#38;D Program of China (grant no. 2017YFD0201400), and the China Postdoctoral Science Foundation (grant no. 2017M620643). Works in the UCLA Institute of Advancement (Suzhou) were supported by the internal grants from Jiangsu Province and Suzhou Industrial Park.

1. Construction of the plasmids expressing the rare-codon-rich marker genes
<ol>
	<li>Select a marker gene that contains an appropriate number of the common codons for the targeted amino acid. 
	NOTE: For L-leucine, the kanamycin resistance gene kanR, which contains 29 leucine codons, of which 27 are common codons, is used for the construction of the selection system13. The gfp gene, which contains 17 common codons out of 19 leucine codons, or the purple protein-encoding gene prancerpurple (ppg), which harbors 14 leucine common codons, is used for the screening system (Supplementary Table 1).</li>
	<li>Replace the common codons in the marker genes with the synonymous rare codon. For L-leucine, replace its codons in kanR, gfp, or ppg with the rare codon CTA, generating kanR-RCs, gfp-RC, or ppg-RC, respectively13 (Supplementary Table 1). 
	NOTE: The frequency of the rare codon in the marker genes will affect the stringency of the selection or screening system. In general, increasing the number of rare codons will increase the stringency of the selection or screening system. To achieve the appropriate selection or screening strength, design a series of marker genes that harbor different numbers of rare codons and compare their effects.</li>
	<li>Generate building blocks of the rare-codon-rich marker genes using tools such as GeneDesign14 (http://54.235.254.95/gd/) for gene synthesis. Alternatively, order the marker genes from commercial gene synthesis services.
	<ol>
		<li>On the GeneDesign page, choose Building block design (constant length overlap).</li>
		<li>Paste the sequences of the rare-codon-rich marker genes in the Sequence box.</li>
		<li>Define the overlap length between the assembly oligos; keep in mind that the default 40 bp works fine for most sequences. 
		NOTE: See the online manual for more instructions on the settings of the other parameters.</li>
		<li>Click the Design building blocks button and order the oligonucleotides listed on the page.</li>
	</ol>
	</li>
	<li>Synthesize the rare-codon-modified genes by polymerase chain reaction (PCR)-based accurate synthesis15.</li>
	<li>Ligate the rare-codon-rich kanR-RC to vector pET-28a, gfp-RC to pSB1C3, and ppg-RC to CPB-37-44116. 
	NOTE: The pET-28a and pSB1C3 plasmid maps are available on the SnapGene online plasmid database (Supplementary Table 1); the CPB-37-441 plasmid map is available on the ATUM chromogenic protein website.
	<ol>
		<li>On ice, add the vector and the marker fragments in a molar ratio of 1:1 to 7.5 &#956;L of assembly mix (see Table of Materials) to a total volume of 10 &#956;L. Incubate the sample at 50 &#176;C for 1 h.</li>
		<li>Transform 5 &#956;L of the assembly product into 50 &#956;L of competent cells (see the Table of Materials) at 42 &#176;C for 30 s.</li>
		<li>Recover the cells in SOC (Super optimal broth with catabolite repression) medium at 37 &#176;C for 1 h, plate them on LB (lysogeny broth) agar medium, and incubate them at 37 &#176;C overnight.</li>
		<li>Inoculate the colony into LB medium and incubate at 37 &#176;C for 8 h.</li>
		<li>Isolate the plasmid using a preferred commercial kit.</li>
	</ol>
	</li>
</ol>
2. Optimizing the selection conditions
<ol>
	<li>Make the parent strain used for mutagenesis into competent cells17.</li>
	<li>Transform 50 &#956;L of the competent cells with 1 &#956;L of plasmid that carries the wild-type kanR, and transform another set of the competent cells with the plasmid containing kanR-RC29 with all leucine codon replaced by the rare codon CTA.</li>
	<li>Add 950 &#956;L of SOC medium and incubate the sample in a shaker at 250 rpm at 37 &#176;C for 1 h.</li>
	<li>Plate 100 &#956;L of the cell culture onto the LB agar medium containing 50 &#956;g&#183;mL-1 kanamycin, and incubate it at 37 &#176;C for approximately 8 h until colonies appear.</li>
	<li>Pick the colonies that harbor the wild-type kanR and the leucine rare-codon-rich kanR-RC29 and use each to inoculate 5 mL of fivefold diluted LB medium (0.2x LB) containing 50 &#956;g&#183;mL-1 kanamycin. Incubate the samples in a shaker at 250 rpm at 37 &#176;C. 
	NOTE: The medium is crucial for the selection system. It should contain just enough carbon and nitrogen to allow expression of the antibiotic resistance protein from the wild-type gene rather than from the rare-codon-modified derivatives. In this case, the L-leucine concentration in 1x LB medium is too high to completely inhibit the protein expression from the rare-codon-rich kanR. Thus, a diluted LB medium with a dilution factor such as 5 is used to generate a clear difference in protein expressions from the wild-type and the rare-codon-rich genes.</li>
	<li>Transfer 200 &#956;L of each of the cell cultures to a 96-well plate in triplicate at defined time points (e.g., 8 h, 16 h, and 24 h). Measure the OD600 (optical density at 600 nm) using a plate reader. 
	NOTE: If a decrease in the cell OD600 cannot be detected for strains harboring the rare-codon-rich marker genes in comparison to the OD600 of the strain harboring the wild-type marker genes, try to increase the amount of rare codon in the marker genes or use a more diluted medium.</li>
	<li>Perform the amino acid feeding assay to test if the expressions of the rare-codon-rich marker genes (e.g., kanR-RC29) can be restored by increasing the concentration of the targeted amino acids. 
	NOTE: For the selection of L-leucine overproducers, L-leucine is used for feeding.
	<ol>
		<li>Inoculate the strains harboring the kanR-RC29 marker gene into 5 mL of the 0.2x LB (containing 50 &#956;g&#183;mL-1 kanamycin) with or without the supply of 1 g&#183;L-1 L-leucine. Inoculate another 5 mL of the 0.2x LB with strains that harbor the wild-type kanR as control. Incubate the samples in a shaker at 250 rpm at 37 &#176;C.</li>
		<li>Measure the OD600 for each culture at defined time points (e.g., 15 h, 17 h, 19 h, and 22 h).</li>
	</ol>
	</li>
</ol>
3. Optimizing the screening conditions
<ol>
	<li>Transform 50 &#956;L of the parent strain used for mutagenesis with 1 &#956;L of plasmid (~50 ng&#183;&#956;L-1) that carries the wild-type gfp or the wild-type ppg. Also, transform the parent strain with the rare-codon-rich derivatives of the marker genes.</li>
	<li>Add 950 &#956;L of SOC medium and incubate the sample in a shaker at 250 rpm at 37 &#176;C for 1 h.</li>
	<li>Plate 100 &#956;L of the cell culture onto the LB agar medium containing the appropriate antibiotics (25 &#956;g&#183;mL-1 chloramphenicol for the gfp plasmid carrying a cmR marker, or 50 &#956;g&#183;mL-1 kanamycin for the ppg plasmid carrying a kanR marker) and incubate overnight at 37 &#176;C.</li>
	<li>Pick one colony that harbors the wild-type gfp or ppg and one colony that harbors the corresponding rare-codon-rich derivative, and transfer them to 5 mL of the properly diluted LB medium individually. Incubate the samples in a shaker at 250 rpm at 37 &#176;C. 
	NOTE: For E. coli strains harboring the leucine rare-codon-rich gfp-RC or ppg-RC, the undiluted LB medium (1x LB) can be used to create significant differences in the expressions of the wild-type and the rare-codon-rich marker genes. Also, inducible promoters are used to drive the expressions of the screening marker genes. Begin the induction when the cells enter the exponential phase to achieve better discriminations.</li>
	<li>For fluorescence markers, transfer 200 &#956;L of each of the cell cultures into a 96-well clear-bottomed black plate in triplicate at defined time points (e.g., 2 h, 4 h, and 6 h). Measure the OD600 and the fluorescence and calculate the fluorescence intensity (the ratio of fluorescence to OD600). For chromogenic markers, measure the color development of the cell cultures. 
	NOTE: If lower fluorescence intensities cannot be detected for strains harboring the gfp-RC in comparison to that of the strains harboring the wild-type gfp, or if a lighter color cannot be detected for cells expressing the purple protein from the ppg-RC than from the wild-type gene, try to increase the number of rare codon on the marker genes or use a more diluted medium.</li>
	<li>Perform the feeding assay (see steps 2.7.1 and 2.7.2). Measure the fluorescence intensity or the color development at defined time points (e.g., 12 h, 18 h, and 24 h).</li>
</ol>
4. Identification of the amino acid overproducers
<ol>
	<li>Inoculate 100 &#956;L of the culture of the mutants into 5 mL of LB medium (2% v/v) and incubate it in a shaker at 250 rpm at 37 &#176;C until the values of OD600 reach 0.4.</li>
	<li>Make the mutants into competent cells17.</li>
	<li>Transform 50 &#956;L of the mutant cells with 1 &#956;L of the plasmid (~50 ng&#183;&#956;L-1) carrying the selection marker kanR-RC29 or the screening markers gfp-RC or ppg-RC. Add 950 &#956;L of SOC medium and rotate the sample in a 37 &#176;C shaker for 1 h.</li>
	<li>Select amino acid overproducers.
	<ol>
		<li>Centrifuge the cell culture at 4,000 x g for 5 min, discard the supernatant and add 5 mL of 0.2x LB medium containing 50 &#956;g&#183;mL-1 kanamycin. Incubate the sample in a 37 &#176;C shaker overnight.</li>
		<li>Plate the overnight culture (e.g., 100 &#956;L, depends on the cell density of the culture) onto 0.2x LB agar medium containing 50 &#956;g&#183;mL-1 kanamycin and incubate at 37 &#176;C for 12 h. 
		NOTE: The colonies developed are the candidates of the targeted amino acid overproducers and, in this case, the L-leucine overproducers.</li>
	</ol>
	</li>
	<li>Screen the amino acid overproducers.
	<ol>
		<li>Plate the appropriate number of cells (e.g., 100 &#956;L) harboring the screening marker (as described in step 4.3) onto the LB agar medium containing the appropriate antibiotic (25 &#956;g&#183;mL-1 chloramphenicol for screening with gfp-RC and 50 &#956;g&#183;mL-1 kanamycin for screening with ppg-RC) and incubate at 37 &#176;C for 8 h.</li>
		<li>Inoculate the LB medium containing the appropriate antibiotic (see step 4.5.1) with each single colony from the plate. Incubate the samples in a shaker at 250 rpm at 37 &#176;C.</li>
		<li>Measure the OD600 and the fluorescence and calculate the fluorescence intensity if gfp-RC is used. Measure the color development of the cell cultures if ppg-RC is used. Note that the strains exhibiting a higher fluorescence intensity or a deeper color than that of the parent strain are the candidate amino acid overproducers and, in this case, the L-leucine overproducers. 
		NOTE: The fluorescence-activated cell sorting is also suitable for identifying single-cell high-producers when the rare-codon-rich fluorescent protein genes are used for screening.</li>
	</ol>
	</li>
	<li>Verify the amino acid productivities of the candidate strains.
	<ol>
		<li>Inoculate 5 mL of LB medium with each of the candidate strains and let the cells grow overnight in a shaker at 250 rpm at 37 &#176;C.</li>
		<li>Harvest the cells from 1 mL of the cell culture by centrifugation at 4,000 x g for 2 min. Discard the supernatant and resuspend the pellet with 1 mL of sterile water.</li>
		<li>Inoculate 20 mL of M9 medium containing 4% glucose with 200 &#956;L of the cell suspension and incubate in a 250 mL shaker at 250 rpm at 37 &#176;C for 24 h.</li>
		<li>Centrifuge 1 mL of the culture medium at 4,000 x g for 5 min. Transfer 200 &#956;L of the supernatant to a clean 1.5 mL tube. Prepare L-leucine solutions (HPLC (high-performance liquid chromatography) grade) of 0.01, 0.05, 0.1, 0.5, and 1 g&#183;L-1 as standards.</li>
		<li>Add 100 &#956;L of 1 mM triethylamine and 100 &#956;L of 1 M phenyl isothiocyanate to the supernatant and the standards, mix them gently, and incubate them at room temperature for 1 h18. 
		CAUTION: Triethylamine and phenyl isothiocyanate can cause severe skin burns and eye damage and is harmful if inhaled. Wear gloves and a mask and, if possible, perform this step in a fume hood.</li>
		<li>Add 400 &#956;L of n-hexane to the same tube and vortex it for 10 s. Filter the lower phase containing the amino acid derivatives through a 0.2 &#956;m polytetrafluoroethylene membrane. 
		CAUTION: n-hexane can cause skin irritation. Wear gloves and protective clothing. If it comes in contact with skin, rinse the skin with plenty of water.</li>
		<li>Prepare mobile phase A by mixing 0.1 M sodium acetate (pH 6.5) and acetonitrile in a 99.3:0.7 volumetric ratio. Prepare acetonitrile (80% v/v) as mobile phase B. Filter all mobile phases through 0.2 &#956;m polytetrafluoroethylene membranes. 
		CAUTION: Acetonitrile is harmful if inhaled and can cause skin and eye irritations. Wear gloves and protective clothing and perform this step in a fume hood.</li>
		<li>Run 1 &#956;L of the sample on an ultra-HPLC equipped with a C18 column according to the elution program in Table 1 with a flow rate of 0.42 mL&#183;min-1 and a column temperature of 40 &#176;C. Detect the targeted amino acids at 254 nm with a diode array detector and calculate their concentrations by mapping the peak areas to the standard curve.</li>
	</ol>
	</li>
</ol>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Time (min)</td>
			<td>Mobile phase A (%)</td>
			<td>Mobile phase B (%)</td>
		</tr>
		<tr>
			<td>0</td>
			<td>98</td>
			<td>2</td>
		</tr>
		<tr>
			<td>3.5</td>
			<td>70</td>
			<td>30</td>
		</tr>
		<tr>
			<td>7</td>
			<td>43</td>
			<td>57</td>
		</tr>
		<tr>
			<td>7.1</td>
			<td>0</td>
			<td>100</td>
		</tr>
		<tr>
			<td>11</td>
			<td>98</td>
			<td>2</td>
		</tr>
	</tbody>
</table>
Table 1: Elution program for the quantification of amino acids.

<ol>
	<li>Tatsumi, N., Inui, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Corynebacterium glutamicum: biology and biotechnology. , (2012).</li><li>Tonouchi, N., Ito, H., Yokota, A., Ikeda, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Present+global+situation+of+amino+acids+in+industry.">Present global situation of amino acids in industry.</a> Amino Acid Fermentation. , 3-14 (2017).</li><li>Gusyatiner, M., Lunts, M., Kozlov, Y., Ivanovskaya, L., Voroshilova, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> DNA coding for mutant isopropylmalate synthase, L-leucine-producing microorganism and method for producing L-leucine. , (2005).</li><li>Park, J. H., Lee, S. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Towards+systems+metabolic+engineering+of+microorganisms+for+amino+acid+production.">Towards systems metabolic engineering of microorganisms for amino acid production.</a> Current Opinion in Biotechnology. 19 (5), 454-460 (2008).</li><li>Norris, R., Lea, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+amino+acid+analogues+in+biological+studies.">The use of amino acid analogues in biological studies.</a> Science Progress. , 65-85 (1976).</li><li>Park, J. H., Lee, S. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fermentative+production+of+branched+chain+amino+acids:+a+focus+on+metabolic+engineering.">Fermentative production of branched chain amino acids: a focus on metabolic engineering.</a> Applied Microbiology and Biotechnology. 85 (3), 491-506 (2010).</li><li>Bach, T. M., Takagi, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Properties,+metabolisms,+and+applications+of+L-proline+analogues.">Properties, metabolisms, and applications of L-proline analogues.</a> Applied Microbiology and Biotechnology. 97 (15), 6623-6634 (2013).</li><li>Crick, F. H. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+genetic+code.">On the genetic code.</a> Science. 139 (3554), 461-464 (1963).</li><li>Plotkin, J. B., Kudla, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synonymous+but+not+the+same:+the+causes+and+consequences+of+codon+bias.">Synonymous but not the same: the causes and consequences of codon bias.</a> Nature Reviews Genetics. 12 (1), 32-42 (2011).</li><li>Dittmar, K. A., S&#248;rensen, M. A., Elf, J., Ehrenberg, M., Pan, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selective+charging+of+tRNA+isoacceptors+induced+by+amino&#8208;acid+starvation.">Selective charging of tRNA isoacceptors induced by amino&#8208;acid starvation.</a> EMBO Reports. 6 (2), 151-157 (2005).</li><li>Elf, J., Nilsson, D., Tenson, T., Ehrenberg, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selective+charging+of+tRNA+isoacceptors+explains+patterns+of+codon+usage.">Selective charging of tRNA isoacceptors explains patterns of codon usage.</a> Science. 300 (5626), 1718-1722 (2003).</li><li>S&#248;rensen, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Charging+levels+of+four+tRNA+species+in+Escherichia+coli+Rel++and+Rel&#8722;+strains+during+amino+acid+starvation:+a+simple+model+for+the+effect+of+ppGpp+on+translational+accuracy.">Charging levels of four tRNA species in Escherichia coli Rel+ and Rel&#8722; strains during amino acid starvation: a simple model for the effect of ppGpp on translational accuracy.</a> Journal of Molecular Biology. 307 (3), 785-798 (2001).</li><li>Zheng, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Utilization+of+rare+codon-rich+markers+for+screening+amino+acid+overproducers.">Utilization of rare codon-rich markers for screening amino acid overproducers.</a> Nature Communications. 9 (1), 3616 (2018).</li><li>Richardson, S. M., Wheelan, S. J., Yarrington, R. M., Boeke, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GeneDesign:+rapid,+automated+design+of+multikilobase+synthetic+genes.">GeneDesign: rapid, automated design of multikilobase synthetic genes.</a> Genome Research. 16 (4), 550-556 (2006).</li><li>Xiong, A. -. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PCR-based+accurate+synthesis+of+long+DNA+sequences.">PCR-based accurate synthesis of long DNA sequences.</a> Nature Protocols. 1 (2), 791-797 (2006).</li><li>Gibson, D. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enzymatic+assembly+of+DNA+molecules+up+to+several+hundred+kilobases.">Enzymatic assembly of DNA molecules up to several hundred kilobases.</a> Nature Methods. 6 (5), 343-345 (2009).</li><li>Green, M. R., Sambrook, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Molecular cloning: a laboratory manual. , (2012).</li><li>Cohen, S. A., Bidlingmeyer, B. A., Tarvin, T. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PITC+derivatives+in+amino+acid+analysis.">PITC derivatives in amino acid analysis.</a> Nature. 320 (6064), 769-770 (1986).</li><li>Zhou, J., Liu, W. J., Peng, S. W., Sun, X. Y., Frazer, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Papillomavirus+capsid+protein+expression+level+depends+on+the+match+between+codon+usage+and+tRNA+availability.">Papillomavirus capsid protein expression level depends on the match between codon usage and tRNA availability.</a> Journal of Virology. 73 (6), 4972-4982 (1999).</li><li>Gregg, C. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rational+optimization+of+tolC+as+a+powerful+dual+selectable+marker+for+genome+engineering.">Rational optimization of tolC as a powerful dual selectable marker for genome engineering.</a> Nucleic Acids Research. 42 (7), 4779-4790 (2014).</li><li>Pelicic, V., Reyrat, J. M., Gicquel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expression+of+the+Bacillus+subtilis+sacB+gene+confers+sucrose+sensitivity+on+mycobacteria.">Expression of the Bacillus subtilis sacB gene confers sucrose sensitivity on mycobacteria.</a> Journal of Bacteriology. 178 (4), 1197-1199 (1996).</li><li>Avcilar-Kucukgoze, I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discharging+tRNAs:+a+tug+of+war+between+translation+and+detoxification+in+Escherichia+coli.">Discharging tRNAs: a tug of war between translation and detoxification in Escherichia coli.</a> Nucleic Acids Research. 44 (17), 8324-8334 (2016).</li><li>Mundhada, H., Schneider, K., Christensen, H. B., Nielsen, A. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+of+high+yield+production+of+L-serine+in+Escherichia+coli.">Engineering of high yield production of L-serine in Escherichia coli.</a> Biotechnology and Bioengineering. 113 (4), 807-816 (2016).</li><li>Makosky, P. C., Dahlberg, A. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spectinomycin+resistance+at+site+1192+in+16S+ribosomal+RNA+of+E.+coli:+an+analysis+of+three+mutants.">Spectinomycin resistance at site 1192 in 16S ribosomal RNA of E. coli: an analysis of three mutants.</a> Biochimie. 69 (8), 885-889 (1987).</li><li>Feng, L., Tumbula-Hansen, D., Toogood, H., S&#246;ll, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expanding+tRNA+recognition+of+a+tRNA+synthetase+by+a+single+amino+acid+change.">Expanding tRNA recognition of a tRNA synthetase by a single amino acid change.</a> Proceedings of the National Academy of Sciences of the United States of America. 100 (10), 5676-5681 (2003).</li><li>Naganuma, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+selective+tRNA+aminoacylation+mechanism+based+on+a+single+G&#8226;+U+pair.">The selective tRNA aminoacylation mechanism based on a single G&#8226; U pair.</a> Nature. 510 (7506), 507 (2014).</li><li>Hoesl, M. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemical+evolution+of+a+bacterial+proteome.">Chemical evolution of a bacterial proteome.</a> Angewandte Chemie International Edition. 54 (34), 10030-10034 (2015).</li><li>Hershberg, R., Petrov, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selection+on+codon+bias.">Selection on codon bias.</a> Annual Review of Genetics. 42, 287-299 (2008).</li><li>Huo, Y. -. X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Conversion+of+proteins+into+biofuels+by+engineering+nitrogen+flux.">Conversion of proteins into biofuels by engineering nitrogen flux.</a> Nature Biotechnology. 29, 346 (2011).</li></ol>

The authors have nothing to disclose.

The number of rare codons in the marker genes and the selection or screening medium are critical to inhibit protein expressions from the rare-codon-modified marker genes. If no significant difference can be detected between protein expressions from the wild-type marker genes and their derivatives, increasing the number of rare codons or using a nutrient-limited medium may amplify the differences. However, if the inhibition effect is too strong, the protein expressions may not be recovered even by extra feeding of the cor...

The current production of amino acids relies heavily on fermentation. However, the titers and yields for most amino acid production strains are below the rising demands of the global amino acid market that is worth billions of dollars1,2. Obtaining high-performance amino acid overproducers are critical for the upgrade of the amino acid industry.
Traditional strategy to identify amino acid overproducers exploits the competitions between amino acids and their analogs in protein synthesis3,4. These analogs are able to charge the tRNAs that recognize the corresponding amino acids and thus inhibit the elongations of the peptide chains, leading to arrested growth or cell death5. One way to resist the analog stresses is to increase the concentrations of intracellular amino acids. The enriched amino acids will outcompete the analogs for the finite tRNAs and ensure the correct synthesis of functional proteins. Therefore, strains that survive the analogs can be selected and are likely the overproducers of the corresponding amino acids.
Although proved successful in selecting overproducers for amino acids such as L-leucine6, the analog-based strategy suffers from severe drawbacks. One major concern is the analog resistance originated from the process of mutagenesis or through spontaneous mutations. Strains with resistance can escape the selection by blocking, exporting, or degrading the analogs5. Another concern is the toxic side effects of the analogs on other cellular processes7. As a consequence, strains that survive the analog selection may not be the amino acid overproducers, while the desired overproducers could be falsely exterminated due to the negative side effects.
Here, a novel strategy based on the law of codon bias is presented in order to achieve accurate and rapid identifications of amino acid overproducers. Most amino acids are encoded by more than one nucleotide&#160;triplet that is favored differently by the host organisms8,9. Some codons are rarely used in the coding sequences and are referred to as the rare codons. Their translations into amino acids rely on the cognate tRNAs that carry the corresponding amino acids. However, the tRNAs that recognize rare codons usually have much lower abundances than the tRNAs of the common codons10,11. Consequently, these rare tRNAs are less likely to capture the free amino acids in the competitions with other isoacceptors, and translations of the rare-codon-rich sequences begin to decelerate or even are terminated when the amounts of amino acids are limited10. The translations could, theoretically, be restored if there is an amino acid surplus after charging the synonymous common tRNAs due to overproductions or extra feedings of the corresponding amino acids12. If the rare-codon-rich gene encodes a selection or screening marker, strains exhibiting the corresponding phenotypes can then be readily identified and are likely the overproducers of the targeted amino acids.
The above strategy is applied to establish a selection and a screening system for the identification of amino acid overproducers. The selection system uses antibiotic resistance genes (e.g., kanR) as markers while the screening system uses the genes encoding fluorescent (e.g., green fluorescent protein [GFP]) or chromogenic (e.g., PrancerPurple) proteins. The marker genes in both systems are modified by replacing defined numbers of the common codons for the targeted amino acid with its synonymous rare alternative. Strains in the mutation library that harbor the rare-codon-rich marker gene are selected or screened under proper conditions, and the overproducers of the targeted amino acids can be readily identified. The workflow begins with the construction of the rare-codon-rich marker gene system, followed by the optimization of the working conditions, and then the identification and verification of the amino acid overproducers. This analog-independent strategy is based on the dogma in protein translation and has been practically verified to enable accurate and rapid identifications of amino acid overproducers. Theoretically, it could be directly employed to amino acids with rare codons and to all microorganisms. In all, the rare-codon-based strategy will serve as an efficient alternative to the conventional analog-based approach when proper analogs for specific amino acids are unavailable, or when a high false positive rate is the major concern. The protocol below uses leucine rare codon to demonstrate this strategy in identifying Escherichia coli L-leucine overproducers.

<table>
	<tbody>
		<tr>
			<td>Acetonitrile</td>
			<td>Thermo</td>
			<td>51101</td>
			<td></td>
		</tr>
		<tr>
			<td>EasyPure HiPure Plasmid MiniPrep Kit</td>
			<td>Transgen</td>
			<td>EM111-01</td>
			<td></td>
		</tr>
		<tr>
			<td>EasyPure Quick Gel Extraction Kit</td>
			<td>Transgen</td>
			<td>EG101-01</td>
			<td></td>
		</tr>
		<tr>
			<td>Gibson assembly master mix</td>
			<td>NEB</td>
			<td>E2611S</td>
			<td></td>
		</tr>
		<tr>
			<td>Isopropyl &#946;-D-1-thiogalactopyranoside</td>
			<td>Solarbio</td>
			<td>I8070</td>
			<td></td>
		</tr>
		<tr>
			<td>L-leucine</td>
			<td>Sigma</td>
			<td>L8000</td>
			<td></td>
		</tr>
		<tr>
			<td>Microplate reader</td>
			<td>Biotek</td>
			<td>Synergy 2</td>
			<td></td>
		</tr>
		<tr>
			<td>n-hexane</td>
			<td>Thermo</td>
			<td>H3061</td>
			<td></td>
		</tr>
		<tr>
			<td>Phenyl isothiocyanate</td>
			<td>Sigma</td>
			<td>P1034</td>
			<td></td>
		</tr>
		<tr>
			<td>PrancerPurple CPB-37-441</td>
			<td>ATUM</td>
			<td>CPB-37-441</td>
			<td></td>
		</tr>
		<tr>
			<td>TransStar FastPfu Fly DNA polymerase</td>
			<td>Transgen</td>
			<td>AP231-01</td>
			<td></td>
		</tr>
		<tr>
			<td>Triethylamine</td>
			<td>Sigma</td>
			<td>T0886</td>
			<td></td>
		</tr>
		<tr>
			<td>Ultra-high performance liquid chromatography</td>
			<td>Agilent</td>
			<td>1290 Infinity II</td>
			<td></td>
		</tr>
		<tr>
			<td>Wild type C. glutamicum</td>
			<td>ATCC</td>
			<td>13032</td>
			<td></td>
		</tr>
		<tr>
			<td>XL10-Gold E. coli competent cell</td>
			<td>Agilent</td>
			<td>200314</td>
			<td></td>
		</tr>
		<tr>
			<td>ZORBAX RRHD Eclipse Plus C18 column</td>
			<td>Agilent</td>
			<td>959759-902K</td>
			<td></td>
		</tr>
	</tbody>
</table>

identifying amino acid overproducers using rare-codon-rich markers

To satisfy the ever-growing market for amino acids, high-performance production strains are needed. The amino acid overproducers are conventionally identified by harnessing the competitions between amino acids and their analogs. However, this analog-based method is of low accuracy, and proper analogs for specific amino acids are limited. Here, we present an alternative strategy that enables an accurate, sensitive, and high-throughput screening of amino acid overproducers using rare-codon-rich markers. This strategy is inspired by the phenomenon of codon usage bias in protein translation, for which codons are categorized into common or rare ones based on their frequencies of occurrence in the coding DNA. The translation of rare codons depends on their corresponding rare transfer RNAs (tRNAs), which cannot be fully charged by the cognate amino acids under starvation. Theoretically, the rare tRNAs can be charged if there is a surplus of the amino acids after charging the synonymous common isoacceptors. Therefore, retarded translations caused by rare codons could be restored by feeding or intracellular overproductions of the corresponding amino acids. Under this assumption, a selection or screening system for identifying amino acid overproducers is established by replacing the common codons of the targeted amino acids with their synonymous rare alternatives in the antibiotic resistance genes or the genes encoding fluorescent or chromogenic proteins. We show that the protein expressions can be greatly hindered by the incorporation of rare codons and that the levels of proteins correlate positively with the amino acid concentrations. Using this system, overproducers of multiple amino acids can be readily screened out from mutation libraries. This rare-codon-based strategy only requires a single modified gene, and the host is less likely to escape the selection than in other methods. It offers an alternative approach for obtaining amino acid overproducers.

For the selection system, a sharp decrease in OD600 for strains harboring the rare-codon-rich antibiotic resistance gene should be observed in comparison to the strain harboring the wild-type antibiotic resistance gene when cultured in a suitable medium (Figure 1a). Under the same conditions, the decrease in cell OD600 becomes more obvious as the number of rare codons in the antibiotic resistance gene increases (Figu...

Watch this Scientific Journal Video about Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers at JoVE.com

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

This study presents an alternative strategy to the conventional toxic analog-based method in identifying amino acid overproducers by using rare-codon-rich markers to achieve accuracy, sensitivity, and high-throughput simultaneously.

To satisfy the ever-growing market for amino acids, high-performance production strains are needed. The amino acid overproducers are conventionally ...

identifying-amino-acid-overproducers-using-rare-codon-rich-markers

Research

JoVE Journal

Biochemistry

7.4K Views.  Beijing Institute of Technology. This study presents an alternative strategy to the conventional toxic analog-based method in identifying amino acid overproducers by using rare-codon-rich markers to achieve accuracy, sensitivity, and high-throughput simultaneously.

Video: Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Method for Identifying Small Molecule Inhibitors of the Protein-protein Interaction Between HCN1 and TRIP8b

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are expressed ubiquitously throughout the brain, where they function to regulate the excitability of neurons. The subcellular distribution of these channels in pyramidal neurons of hippocampal area CA1 is regulated by tetratricopeptide repeat-containing Rab8b interacting protein (TRIP8b), an auxiliary subunit. Genetic knockout of HCN pore forming subunits or TRIP8b, both lead to an increase in antidepressant-like behavior, suggesting that limiting the function of HCN channels may be useful as a treatment for Major Depressive Disorder (MDD). Despite significant therapeutic interest, HCN channels are also expressed in the heart, where they regulate rhythmicity. To circumvent off-target issues associated with blocking cardiac HCN channels, our lab has recently proposed targeting the protein-protein interaction between HCN and TRIP8b in order to specifically disrupt HCN channel function in the brain. TRIP8b binds to HCN pore forming subunits at two distinct interaction sites, although here the focus is on the interaction between the tetratricopeptide repeat (TPR) domains of TRIP8b and the C terminal tail of HCN1. In this protocol, an expanded description of a method for purifying TRIP8b and executing a high throughput screen to identify small molecule inhibitors of the interaction between HCN and TRIP8b, is described. The method for high throughput screening utilizes a Fluorescence Polarization (FP) -based assay to monitor the binding of a large TRIP8b fragment to a fluorophore-tagged eleven amino acid peptide corresponding to the HCN1 C terminal tail. This method allows &#39;hit&#39; compounds to be identified based on the change in the polarization of emitted light. Validation assays are then performed to ensure that &#39;hit&#39; compounds are not artifactual.

The interaction between HCN channels and their auxiliary subunit has been identified as a therapeutic target in Major Depressive Disorder. Here, a fluorescence polarization-based method for identifying small molecule inhibitors of this protein-protein interaction, is presented.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are expressed ubiquitously throughout the brain, where they function to regulate the ...

Voltage-clamp Fluorometry in Xenopus Oocytes Using Fluorescent Unnatural Amino Acids

Voltage-Clamp Fluorometry (VCF) has been the technique of choice to investigate the structure and function of electrogenic membrane proteins where real-time measurements of fluorescence and currents simultaneously report on local rearrangements and global function, respectively1. While high-resolution structural techniques such as cryo-electron microscopy or X-ray crystallography provide static images of the proteins of interest, VCF provides dynamic structural data that allows us to link the structural rearrangements (fluorescence) to dynamic functional data (electrophysiology). Until recently, the thiol-reactive chemistry used for site-directed fluorescent labeling of the proteins restricted the scope of the approach because all accessible cysteines, including endogenous ones, will be labeled. It was thus required to construct proteins free of endogenous cysteines. Labeling was also restricted to sites accessible from the extracellular side. This changed with the use of Fluorescent Unnatural Amino Acids (fUAA) to specifically incorporate a small fluorescent probe in response to stop codon suppression using an orthogonal tRNA and tRNA synthetase pair2. The VCF improvement only requires a two-step injection procedure of DNA injection (tRNA/synthetase pair) followed by RNA/fUAA co-injection. Now, labelling both intracellular and buried sites is possible, and the use of VCF has expanded significantly. The VCF technique thereby becomes attractive for studying a wide range of proteins and &#8211; more importantly &#8211; allows investigating numerous cytosolic regulatory mechanisms.

Voltage-clamp Fluorometry in Xenopus Oocytes Using Fluorescent Unnatural Amino Acids

This article describes an enhancement of conventional Voltage-Clamp Fluorometry (VCF) where Fluorescent Unnatural Amino Acids (fUAA) are used instead of maleimide dyes, to probe structural rearrangements in ion channels. The procedure includes Xenopus oocyte DNA injection, RNA/fUAA coinjection, and simultaneous current and fluorescence measurements.

Voltage-Clamp Fluorometry (VCF) has been the technique of choice to investigate the structure and function of electrogenic membrane proteins where ...

Hydrolysis of a Ni-Schiff-Base Complex Using Conditions Suitable for Retention of Acid-labile Protecting Groups

Unnatural amino acids, amino acids containing side-chain functionalities not commonly seen in nature, are increasingly found in synthetic peptide sequences. Synthesis of some unnatural amino acids often includes the use of a precursor consisting of a Schiff-base stabilized by a nickel cation. Unnatural side-chains can be installed on an amino acid backbone found in this Schiff-base complex. The resulting unnatural amino acid can then be isolated from this complex using hydrolysis of the Schiff-base, typically by employing reflux in strongly acidic solution. These highly acidic conditions may remove acid-labile side-chain protecting groups necessary for the unnatural amino acids to be used in microwave-assisted solid-phase peptide synthesis. In this work, we present an efficient hydrolysis and subsequent Fmoc protection of an amino acid isolated from a Ni-Schiff base complex. Hydrolysis conditions presented in this work are suitable for retention of acid-labile side-chain protecting groups and may be adaptable to a variety of unnatural amino acid substrates.

Here, we present an efficient hydrolysis and subsequent Fmoc protection of an amino acid isolated from a Ni-Schiff-base complex. Hydrolysis conditions presented here are suitable for use when retention of acid-labile side-chain protecting groups is required. This technique may be adaptable to a variety of unnatural amino acid substrates.

Unnatural amino acids, amino acids containing side-chain functionalities not commonly seen in nature, are increasingly found in synthetic peptide ...

Kinetic Screening of Nuclease Activity using Nucleic Acid Probes

Nucleases are a class of enzymes that break down nucleic acids by catalyzing the hydrolysis of the phosphodiester bonds that link the ribose sugars. Nucleases display a variety of vital physiological roles in prokaryotic and eukaryotic organisms, ranging from maintaining genome stability to providing protection against pathogens. Altered nuclease activity has been associated with several pathological conditions including bacterial infections and cancer. To this end, nuclease activity has shown great potential to be exploited as a specific biomarker. However, a robust and reproducible screening method based on this activity remains highly desirable.
Herein, we introduce a method that enables screening for nuclease activity using nucleic acid probes as substrates, with the scope of differentiating between pathological and healthy conditions. This method offers the possibility of designing new probe libraries, with increasing specificity, in an iterative manner. Thus, multiple rounds of screening are necessary to refine the probes&#39; design with enhanced features, taking advantage of the availability of chemically modified nucleic acids. The considerable potential of the proposed technology lies in its flexibility, high reproducibility, and versatility for the screening of nuclease activity associated with disease conditions. It is expected that this technology will allow the development of promising diagnostic tools with a great potential in the clinic.

Altered nuclease activity has been associated with different human conditions, underlying its potential as a biomarker. The modular and easy to implement screening methodology presented in this paper allows the selection of specific nucleic acid probes for harnessing nuclease activity as a biomarker of disease.

Nucleases are a class of enzymes that break down nucleic acids by catalyzing the hydrolysis of the phosphodiester bonds that link the ribose sugars. ...

Isolation of Histone from Sorghum Leaf Tissue for Top Down Mass Spectrometry Profiling of Potential Epigenetic Markers

Histones belong to a family of highly conserved proteins in eukaryotes. They pack DNA into nucleosomes as functional units of chromatin. Post-translational modifications (PTMs) of histones, which are highly dynamic and can be added or removed by enzymes, play critical roles in regulating gene expression. In plants, epigenetic factors, including histone PTMs, are related to their adaptive responses to the environment. Understanding the molecular mechanisms of epigenetic control can bring unprecedented opportunities for innovative bioengineering solutions. Herein, we describe a protocol to isolate the nuclei and purify histones from sorghum leaf tissue. The extracted histones can be analyzed in their intact forms by top-down mass spectrometry (MS) coupled with online reversed-phase (RP) liquid chromatography (LC). Combinations and stoichiometry of multiple PTMs on the same histone proteoform can be readily identified. In addition, histone tail clipping can be detected using the top-down LC-MS workflow, thus, yielding the global PTM profile of core histones (H4, H2A, H2B, H3). We have applied this protocol previously to profile histone PTMs from sorghum leaf tissue collected from a large-scale field study, aimed at identifying epigenetic markers of drought resistance. The protocol could potentially be adapted and optimized for chromatin immunoprecipitation-sequencing (ChIP-seq), or for studying histone PTMs in similar plants.

The protocol has been developed to effectively extract intact histones from sorghum leaf materials for profiling of histone post-translational modifications that can serve as potential epigenetic markers to aid engineering drought resistant crops.

Histones belong to a family of highly conserved proteins in eukaryotes. They pack DNA into nucleosomes as functional units of chromatin. ...

Estimation of Plant Biomass Lignin Content using Thioglycolic Acid (TGA)

Lignin is a natural polymer that is the second most abundant polymer on Earth after cellulose. Lignin is mainly deposited in plant secondary cell walls and is an aromatic heteropolymer primarily composed of three monolignols with significant industrial importance. Lignin plays an important role in plant growth and development, protects&#160;from biotic and abiotic stresses, and in the quality of animal fodder, the wood, and industrial lignin products. Accurate estimation of lignin content is essential for both fundamental understanding of the lignin biosynthesis and industrial applications of biomass. The thioglycolic acid (TGA) method is a highly reliable method of estimating the total lignin content in the plant biomass. This method estimates the lignin content by forming thioethers with the benzyl alcohol groups of lignin, which are soluble in alkaline conditions and insoluble in acidic conditions. The total lignin content is estimated using a standard curve generated from commercial bamboo lignin.

Estimation of Plant Biomass Lignin Content using Thioglycolic Acid TGA

Here, we present a modified TGA method for estimation of lignin content in herbaceous plant biomass. This method estimates the lignin content by forming specific thioether bonds with lignin and presents an advantage over the Klason method, as it requires a relatively small sample for lignin content estimation.

Lignin is a natural polymer that is the second most abundant polymer on Earth after cellulose. Lignin is mainly deposited in plant secondary cell walls ...

Optimized Incorporation of Alkynyl Fatty Acid Analogs for the Detection of Fatty Acylated Proteins using Click Chemistry

Fatty acylation, the covalent addition of saturated fatty acids to protein substrates, is important in regulating a myriad of cellular functions in addition to its implications in cancer and neurodegenerative diseases. Recent developments in fatty acylation detection methods have enabled efficient and non-hazardous detection of fatty acylated proteins, particularly through the use of click chemistry with bio-orthogonal labeling. However, click chemistry detection can be limited by the poor solubility and potential toxic effects of adding long chain fatty acids to cell culture. Described here is a labeling approach with optimized delivery using saponified fatty acids in combination with fatty-acid free BSA, as well as delipidated media, which can improve detection of hard to detect fatty acylated proteins. This effect was most pronounced with the alkynyl-stearate analog, 17-ODYA, which has been the most commonly used fatty acid analog in click chemistry detection of acylated proteins. This modification will improve cellular incorporation and increase sensitivity to acylated protein detection. In addition, this approach can be applied in a variety of cell types and combined with other assays such as pulse-chase analysis, stable isotope labeling with amino acids in cell culture, and mass spectrometry for quantitative profiling of fatty acylated proteins.

The study of fatty acylation has important implications in cellular protein interactions and diseases. Presented here is a modified protocol to improve click chemistry detection of fatty acylated proteins, which can be applied in various cell types and combined with other assays, including pulse-chase and mass spectrometry.

Fatty acylation, the covalent addition of saturated fatty acids to protein substrates, is important in regulating a myriad of cellular functions in ...

Folding and Probing of Nucleic Acid Constructs

Predicting Amino Acid Preferences of Protein-Protein Binding Interfaces

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Many protein-protein interactions involve the binding of short protein segments to peptide-binding domains. Usually, such interactions require the recognition of linear motifs with variable conservation. The combination of highly conserved and more variable regions in the same ligands often contributes to the multispecificity of binding, a common property of enzymes and cell signaling proteins. Characterization of amino acid preferences of peptide-binding domains is important for the design of mediators of protein-protein interactions (PPIs). Computational methods are an efficient alternative to the often costly and cumbersome experimental techniques, enabling the design of potential mediators that can be later validated in downstream experiments. Here, we described a methodology using the Pepspec application of the Rosetta molecular modeling package to predict the amino acid preferences of peptide-binding domains. This methodology is useful when the structure of the receptor protein and the nature of the peptide ligand are both known or can be inferred. The methodology starts with a well-characterized anchor from the ligand, which is extended by randomly adding amino acid residues. The binding affinity of peptides generated this way is then evaluated by flexible-backbone peptide docking in order to select the peptides with the best predicted binding scores. These peptides are then used to calculate amino acid preferences and to optionally compute a position-weight matrix (PWM) that can be used in further studies. To illustrate the application of this methodology, we used the interaction between subunits of human interferon regulatory factor 5 (IRF5), previously known to be multispecific but globally guided by a short conserved motif called pLxIS. The estimated amino acid preferences were consistent with previous knowledge about the IRF5 binding surface. Positions occupied by phosphorylatable serine residues exhibited a high frequency of aspartate and glutamate, likely because their negatively charged side chains are similar to phosphoserine.

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

We describe a methodology based on sequence diversification to estimate the amino acid preferences of multispecific binding sites in protein-protein interactions (PPIs). In this strategy, thousands of potential peptide ligands are generated and screened in silico, thus overcoming some limitations of available experimental methods.

Many protein-protein interactions involve the binding of short protein segments to peptide-binding domains. Usually, such interactions require the ...

In Silico Structural Analysis of Protein Carbonylation by Lipid Derivatives

Synthesizing Amino Acids Modified with Reactive Carbonyls in Silico to Assess Structural Effects Using Molecular Dynamics Simulations

Protein carbonylation by reactive aldehydes derived from lipid peroxidation leads to cross-linking, oligomerization, and aggregation of proteins, causing intracellular damage, impaired cell functions, and, ultimately, cell death. It has been described in aging and several age-related chronic conditions. However, the basis of structural changes related to the loss of function in protein targets is still not well understood. Hence, a route to the in silico construction of new parameters for amino acids carbonylated with reactive carbonyl species derived from fatty acid oxidation is described. The Michael adducts for Cys, His, and Lys with 4-hydroxy-2-nonenal (HNE), 4-hydroxy-2-hexenal (HHE), and a furan ring form for 4-Oxo-2-nonenal (ONE), were built, while malondialdehyde (MDA) was directly attached to each residue. The protocol describes details for the construction, geometry optimization, assignment of charges, missing bonds, angles, dihedral angles parameters, and its validation for each modified residue structure. As a result, structural effects induced by the carbonylation with these lipid derivatives have been measured by molecular dynamics simulations on different protein systems such as the thioredoxin enzyme, bovine serum albumin and the membrane Zu-5-ankyrin domain employing root-mean-square deviation (RMSD), root mean square fluctuation (RMSF), structural secondary prediction (DSSP) and the solvent-accessible surface area analysis (SASA), among others.

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function

Here, we describe a protocol for the optimization and parameterization of amino acid residues modified with reactive carbonyl species, adaptable to protein systems. The protocol steps include structure design and optimization, charge assignments, parameter construction, and preparation of protein systems.

Protein carbonylation by reactive aldehydes derived from lipid peroxidation leads to cross-linking, oligomerization, and aggregation of proteins, causing ...