This work was supported by a SC INBRE grant from the National Institute of General Medical Science - NIH (P20GM103499 to R.G.) and grants CA555536 &#38; CA154664 from the National Cancer Institute to P.H.H. This program was supported in part by a grant to the College of Charleston from the Howard Hughes Medical Institute through the Pre-college &#38; Undergraduate Science Education Program and by grants from the National Center for Research Resources (5 P20 RR016461) and the National Institute of General Medical Sciences (8 P20 GM103499) from the National Institutes of Health.

1. Culture and metabolic labeling
<ol>
	<li>Poke once the center of the cap of a sterile 1.5 mL micro-centrifuge tubes with a 18-gauge needle to allow proper aeration. Inoculate 500 &#181;L of supplemented sterile 7H9 broth with 5 &#181;L of M. smegmatis from a starter culture grown overnight12. 
	NOTE: The recipe for one liter of 7H9 broth is: 4.7 g Commercial 7H9 powder, 2 mL Glycerol, 1 mL Tween 80, 0.85 g NaCl, 5 g Albumin, 2 g Dextrose, H2O (to bring total volume to 1 L).
	<ol>
		<li>(CAUTION) Following standard radioprotection practices, spike the culture media with 20 &#181;Ci/mL of [32P] Na2HPO4. Grow bacteria at 37 &#176;C and 1,200 rpm agitation, in a shaker incubator placed behind a 9-mm thick acrylic shield.</li>
	</ol>
	</li>
	<li>At midlog phase (O.D.600 nm ~0.5), transfer the entire culture into a 2-mL screw-cap tube and pellet radioactive bacteria at room temperature by centrifuging for 2 min at 10,000 x g. Collect supernatant containing unincorporated radioactive orthophosphate in appropriate waste container.</li>
</ol>
2. Preparation of total RNAs
NOTE: Total RNAs are extracted from bacterial pellets using a commercial RNA extraction reagent (containing guanidinium thiocyanate, phenol and chloroform) following the manufacturer&#39;s protocol.
<ol>
	<li>Add 1 mL of commercial RNA extraction reagent and approximately 200 &#181;L of glass beads onto the pellet. Cap the tube securely and disrupt the bacterial in a homogenizer for 2 min under maximum agitation, (setting number five on chosen instrument (see the Table of Materials)).</li>
	<li>Centrifuge sample at 12,000 x g for 10 min at 4 &#176;C. Transfer the supernatant to a new 2-mL tube and discard the beads appropriately. Add 0.2 mL of chloroform and shake tube vigorously by hand for 15 s. Centrifuge at 12,000 x g for 15 min at 4 &#176;C.</li>
	<li>Collect the aqueous phase of the sample into a new tube by angling the tube at 45&#176;. Avoid drawing any of the interphase or organic layer. Add 2 &#181;L of colored precipitant and 0.5 mL of 100% isopropanol. Shake the tube vigorously by hand for 5 s. Centrifuge at 12,000 x g for 10 min at 4&#176;C.</li>
	<li>Remove the supernatant from the tube and discard appropriately as the liquid fraction may contain traces of radioactivity. Air dry pellet for 5 min then resuspend in 200 &#181;L of 2X saline-sodium citrate (SSC), 0.1% (w/v) sodium dodecyl sulfate (SDS) final. 
	NOTE: The composition of stock 20 X SSC is 3.0 M NaCl, 0.3 M sodium citrate, pH 7.0.</li>
</ol>
3. Preparation of 96 well printer plates
NOTE: tRNA microarrays are manually printed with forty two 70-mer DNA oligonucleotides complementary to the 3&#39; end of each M. smegmatis tRNA (terminal CCA excluded) using an eight-pin arrayer. The sequences of the DNA oligonucleotide probes as well as the probe layout in the well-plate and the array are provided (Supplementary File 1- sheet 1 to 3 respectively).
<ol>
	<li>Design DNA probes by first retrieving tRNA sequences or tRNA encoding genes from tRNA databases such as the Genomic tRNA Database13. Trim conserved 3&#39; end CCA if encoded. Reverse complement the resulting sequence. Order probe based on the first 70 nucleotides.</li>
	<li>Resuspend dry DNA probes in water. Adjust probes concentration to 100 &#181;M. In a 96 well-plate, prepare 120 &#181;L of 50 &#181;M oligos in 3X SSC, 0.01% (w/v) SDS final (dilute 60 &#181;L of stock probes in individual well with 60 &#181;L of 6X SSC , 0.01% (w/v) SDS.</li>
	<li>Cover plate with tin foil to prevent evaporation or contamination, freeze immediately and keep at -20 &#176;C until needed.</li>
</ol>
4. Array printing
<ol>
	<li>Thaw the 96-well plate at room temperature (takes approximately 20 min).</li>
	<li>Label amine-coated glass slides with a diamond pen. Place slides into indexing unit. Follow the grid placements and do as follows.
	<ol>
		<li>Carefully dip the replicator pins in the wells.</li>
		<li>Gently print the array on the glass slides, using minimal pressure (you will feel a small resistance). Continue printing without cleaning the arrayer until finished with block A.</li>
	</ol>
	</li>
	<li>When ready to move on to the next block, follow the washing procedure described below.
	<ol>
		<li>Dip replicator in the 5% bleach and gently shake.</li>
		<li>Press replicator into absorbent paper.</li>
		<li>Dip replicator in the distilled water, gently shake, and press into paper. Repeat this step once.</li>
		<li>Dip replicator in isopropanol, gently shake, and press into the paper.</li>
		<li>Dry the replicator on the fan for about 20 s before moving on to the next block of the 96-well plate. Continue to desired number of prints.</li>
	</ol>
	</li>
	<li>Allow the slides to dry then crosslink the oligos to the slide using a 254-nm UV crosslinker.
	<ol>
		<li>Set the energy level to 999,990 &#181;J/cm2.</li>
		<li>Put the slides face up on a clean surface in the crosslinker. Press &#34;start&#34;.</li>
	</ol>
	</li>
	<li>Block the arrays overnight in 450 mL of blocking solution on a magnetic stirrer, at room temperature and under slow agitation. Collect and reuse blocking solution up to four times. 
	NOTE: The recipe for the blocking solution is: 125 mM phosphate buffer (NaH2PO4/Na2HPO4-) pH 7.2, 2.25% SDS (w/v), 0.5 mM EDTA, 0.5X SSC, 1% BSA (w/v).</li>
	<li>Wash the slides 2 times for 5 min at room temperature in 500 mL of distilled water. Dry the slides by centrifuging for 10 s at room temperature in a microarray centrifuge. Store arrays in a dry and dark place for up to 6 months.</li>
</ol>
5. Array hybridization
<ol>
	<li>Prior to hybridization rinse slides in boiling water and dry by centrifugation (as in 4.6).</li>
	<li>Place array inside a hybridization cassette and load radiolabeled RNA sample.</li>
	<li>Run the automated hybridization-washing station for maximum reproducibility.
	<ol>
		<li>Program steps as following. Condition gaskets for 2 min at 75 &#176;C. Introduce probe at 60 &#176;C. 
		Denature probes and samples 5 min at 90 &#176;C. Hybridize samples for 3 h at 60 &#176;C.
		<ol>
			<li>Wash slides at 50 &#176;C twice with 2X SSC, 0.1% (w/v) SDS, flow 10 s and hold 20 s. Wash slides at 42 &#176;C twice with 0.1X SSC, 0.1% SDS, flow 10 s and hold 20 s. Wash slides at 42 &#176;C twice with 0.1 X SSC, flow 10 s and hold 20 s.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Dry slides by centrifugation (as in 4.6).</li>
</ol>
6. Array quantification
<ol>
	<li>Wrap slides using a thin plastic film. Check slides for radioactive signal using a Geiger counter on its most sensitive setting. Expose slides onto a storage phosphor screen in an exposure cassette at room temperature for 10 to 90 h depending on signal strength. 
	NOTE: As sensitivity of Geiger counters vary from one instrument to another, exposure times must be optimized empirically.</li>
	<li>Scan slide at 50 &#181;m resolution using a phosphorimager. Quantify and background-subtract radioactivity intensities at each probe spot using the free Image J software upgraded with a microarray profiler.</li>
	<li>Organize and process data using an electronic spreadsheet. Generate heat maps using the conditional formatting tool. Represent for example each probe signal as a fraction (expressed in &#8240;) of the total probe signal.</li>
</ol>

<ol>
	<li>Emilsson, V., Kurland, C. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth+rate+dependence+of+transfer+RNA+abundance+in+Escherichia+coli.">Growth rate dependence of transfer RNA abundance in Escherichia coli.</a> EMBO J. 9 (13), 4359-4366 (1990).</li><li>Dittmar, K. A., Goodenbour, J. 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=Tissue-specific+differences+in+human+transfer+RNA+expression.">Tissue-specific differences in human transfer RNA expression.</a> PLoS Genet. 2 (12), e221 (2006).</li><li>Pavon-Eternod, M., Gomes, S., Geslain, R., Dai, Q., Rosner, M. R., 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=tRNA+over-expression+in+breast+cancer+and+functional+consequences.">tRNA over-expression in breast cancer and functional consequences.</a> Nucleic Acids Res. 37 (21), 7268-7280 (2009).</li><li>Gieg&#233;, R., J&#252;hling, F., P&#252;tz, J., Stadler, P., Sauter, C., Florentz, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structure+of+transfer+RNAs:+similarity+and+variability.">Structure of transfer RNAs: similarity and variability.</a> Wiley Interdiscip Rev RNA. 3 (1), 37-61 (2012).</li><li>Machnicka, M. A., Olchowik, A., Grosjean, H., Bujnicki, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Distribution+and+frequencies+of+post-transcriptional+modifications+in+tRNAs.">Distribution and frequencies of post-transcriptional modifications in tRNAs.</a> RNA Biol. 11 (12), 1619-1629 (2014).</li><li>Torres, A. G., Pi&#241;eyro, D., Rodr&#237;guez-Escrib&#224;, M., Camacho, N., Reina, O., Saint-L&#233;ger, A., Filonava, L., Batlle, E., Ribas de Pouplana, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inosine+modifications+in+human+tRNAs+are+incorporated+at+the+precursor+tRNA+level.">Inosine modifications in human tRNAs are incorporated at the precursor tRNA level.</a> Nucleic Acids Res. 43 (10), 5145-5157 (2015).</li><li>Cognat, V., Deragon, J. M., Vinogradova, E., Salinas, T., Remacle, C., Mar&#233;chal-Drouard, L. <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+evolution+and+expression+of+Chlamydomonas+reinhardtii+nucleus-encoded+transfer+RNA+genes.">On the evolution and expression of Chlamydomonas reinhardtii nucleus-encoded transfer RNA genes.</a> Genetics. 179 (1), 113-123 (2008).</li><li>Zheng, G., Qin, Y., Clark, W. C., Dai, Q., Yi, C., He, C., 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=Efficient+and+quantitative+high-throughput+tRNA+sequencing.">Efficient and quantitative high-throughput tRNA sequencing.</a> Nat Methods. 12 (9), 835-837 (2015).</li><li>Grelet, S., McShane, A., Hok, E., Tomberlin, J., Howe, P. H., Geslain, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SPOt:+A+novel+and+streamlined+microarray+platform+for+observing+cellular+tRNA+levels.">SPOt: A novel and streamlined microarray platform for observing cellular tRNA levels.</a> PLoS One. 12 (5), e0177939 (2017).</li><li>Eriani, G., Karam, J., Jacinto, J., Morris Richard, E., Geslain, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MIST,+a+Novel+Approach+to+Reveal+Hidden+Substrate+Specificity+in+Aminoacyl-tRNA+Synthetases.">MIST, a Novel Approach to Reveal Hidden Substrate Specificity in Aminoacyl-tRNA Synthetases.</a> PLoS One. 10 (6), e0130042 (2015).</li><li>Grelet, S., McShane, A., Geslain, R., Howe, P. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pleiotropic+Roles+of+Non-Coding+RNAs+in+TGF-&#946;-Mediated+Epithelial-Mesenchymal+Transition+and+Their+Functions+in+Tumor+Progression.">Pleiotropic Roles of Non-Coding RNAs in TGF-&#946;-Mediated Epithelial-Mesenchymal Transition and Their Functions in Tumor Progression.</a> Cancers. 9 (7), (2017).</li><li>Belanger, A. E., Hatfull, G. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exponential-phase+glycogen+recycling+is+essential+for+growth+of+Mycobacterium+smegmatis.">Exponential-phase glycogen recycling is essential for growth of Mycobacterium smegmatis.</a> J Bacteriol. 181 (21), 6670-6678 (1999).</li><li>Chan, P. P., Lowe, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GtRNAdb:+A+database+of+transfer+RNA+genes+detected+in+genomic+sequence.">GtRNAdb: A database of transfer RNA genes detected in genomic sequence.</a> Nucl. Acids Res. 37 (Database issue), D93-D97 (2009).</li><li>Schmidt, C. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Effect+of+Radioactive+Phosphorus+upon+a+Suspension+of+Escherichia+coli.">The Effect of Radioactive Phosphorus upon a Suspension of Escherichia coli.</a> J Bacteriol. 55 (5), 705-710 (1948).</li></ol>

No conflict of interest declared.

Beta particle emissions are known bacteriostatic and bactericidal agents14, however radiations in the tested range have no significant impact on cell fitness. Scintillation counting showed that the radioactivity is incorporated into 25% of total-cell extracts and subsequently, 1% of purified total RNAs.
The probes&#39; identical sizes, comparable melting temperature and GC content, along with a uniform protocol for macroarray spotting, hybridization and quantification allows for unbiased measurement of tRNA levels directly from spot signals.
SPOt is reproducible and specific. Its large dynamic range and easily adjustable threshold allows profiling low abundant species, such as tRNAs associated with polysomes, simply by prolonging array exposure times9. After the initial investment for the necessary equipment, the running cost per sample, including consumables, averages $15 per samples.
SPOt is applicable to any organism whose genome is available for probe design. Model organisms that are grown in vitro are ideal candidates for metabolic labeling. As mammalian genomes often encode many isodecoders (tRNAs that share identical anticodons but display small differences in their body sequences) probes need to be partially degenerated to preserve homogenous hybridization of close tRNA species. Finally, adherent mammalian cells yield typically lower amounts of total RNA compared to organisms grown in suspension such as M. smegmatis, so cultures need to be substantially scaled up.

Cellular tRNA levels fluctuate according to conditions such as cell type, environment, and stress1,2,3. SPOt, Streamlined Platform for Observing tRNA, is an original, reliable, and straightforward technique that allows fast and precise quantification of transfer RNA levels in laboratory-grown organisms.
tRNAs have remarkably stable secondary and tertiary structures4. They also display numerous post-transcriptional modifications5. These features represent significant structural and sequence roadblocks biasing or sometimes preventing direct and reproducible tRNA profiling using standard benchmark RNA quantification techniques6. Research groups around the world were forced to develop creative but often convoluted techniques to assess cellular tRNA levels. Some of these methods include: (1) two-dimensional electrophoretic separation of metabolically labeled tRNAs combined with methodical spot assignment by Northern blot1; (2) individual quantification by Northern blot using carefully standardized radioactive DNA probes7; (3) post-extraction labeling with cyanine fluorochromes followed by microarray analysis3, and (4) in vitro stripping of tRNA modifications using recombinant demodification enzymes combined with reverse transcription and subsequent high-throughput sequencing8.
SPOt is a simple and original combination of two standard and straightforward approaches: (1) RNA body labeling, which consists in the synthesis, in growing organisms, of radioactive total RNAs and (2) tRNA macroarrays, a systematic and miniaturized genomic tool optimized for tRNA segregation.
Samples are streamlined from living organisms to the quantification platform. They are directly analyzed after extraction and not processed any further which significantly limits biases compared to techniques requiring post-extraction amplification or enzymatic treatments. SPOt is versatile and can be easily combined to polysome fractionation to identify and quantify tRNA subpopulations that are physically associated with translating ribosomes.
The protocol presented here is optimized for Mycobacterium smegmatis, and it was also successfully used to profile tRNAs in Escherichia coli9, Saccharomyces cerevisiae10, mouse, and human cell cultures11.

<table><tbody><tr><td>Glass slide indexing system</td><td>V&amp;amp;P Scientific, Inc.</td><td>VP 470</td><td></td></tr><tr><td>Glass slide arrayer replicator</td><td>V&amp;amp;P Scientific, Inc.</td><td>VP 478</td><td></td></tr><tr><td>96 well microplate indexing system</td><td>V&amp;amp;P Scientific, Inc.</td><td>VP 472</td><td></td></tr><tr><td>Wash and blot station</td><td>V&amp;amp;P Scientific, Inc.</td><td>VP 475</td><td></td></tr><tr><td>Replicator pin dryer</td><td>V&amp;amp;P Scientific, Inc.</td><td>VP 474</td><td></td></tr><tr><td>Amine coated slides</td><td>Molecular Devices</td><td>K2615</td><td></td></tr><tr><td>Hybridizer / Automated hybridization and washing station</td><td>Digilab</td><td>Hyb10022</td><td></td></tr><tr><td>Shaker incubator</td><td>Eppendorf Themomixer</td><td>05-400-200</td><td></td></tr><tr><td>Screw cap 2 ml tubes</td><td>Thermo Scientific</td><td>21-403-201</td><td></td></tr><tr><td>[32P] Na2HPO4</td><td>Perkin Elmer</td><td>NEX011001MC</td><td></td></tr><tr><td>Guanidinium thiocyanate-phenol-chloroform (Trizol)</td><td>Invitrogen</td><td>15596026</td><td></td></tr><tr><td>0.5 mm glass beads</td><td>Research Products International Corp.</td><td>9831</td><td></td></tr><tr><td>Mini bead mill</td><td>VWR</td><td>25-020</td><td></td></tr><tr><td>Storage phosphore screen</td><td>Fujifilm</td><td>BAS-IP SR 0813</td><td></td></tr><tr><td>Phosphorimager</td><td>GE Healthcare</td><td>Typhoon FLA7000</td><td></td></tr><tr><td>DNA oligonucleotides</td><td>IDT</td><td>N/A</td><td></td></tr><tr><td>UV crosslinker</td><td>Spectroline</td><td>Select series 254 nm</td><td></td></tr><tr><td>Microarray centrifuge</td><td>Arrayit Corporation</td><td>MHC110V</td><td></td></tr><tr><td>&lt;em&gt;Mycobacterium smegmatis&lt;/em&gt;</td><td>ATCC</td><td>700084</td><td></td></tr><tr><td>Single-use needles</td><td>BD (Becton Dickinson)</td><td>305185</td><td></td></tr><tr><td>2 ml centrifuge tube</td><td>Fisherbrand</td><td>14-666-317</td><td></td></tr><tr><td>Precipitant (GlucoBlue)</td><td>Invitrogen</td><td>AM9516</td><td></td></tr><tr><td>7H9 broth</td><td>Difco</td><td>271310</td><td></td></tr><tr><td>Chloroform</td><td>Fisher Chemicals</td><td>C298-500</td><td></td></tr><tr><td>Isopropanol</td><td>Fisher Chemicals</td><td>A451-4</td><td></td></tr><tr><td>20 X SSC</td><td>Lonza</td><td>51205</td><td></td></tr><tr><td>SDS</td><td>Fisher Bioreagents</td><td>BP166-100</td><td></td></tr><tr><td>hybridisation cassette</td><td>GE Healthcare</td><td>63-0035-44</td><td></td></tr><tr><td>Glycerol</td><td>Fisher Scientific</td><td>BP229-1</td><td></td></tr><tr><td>Tween 80</td><td>Amresco</td><td>M126-100ML</td><td></td></tr><tr><td>NaCl</td><td>Fisher Scientific</td><td>BP358-212</td><td></td></tr><tr><td>Albumin</td><td>Spectrum Chemicals</td><td>A3611</td><td></td></tr><tr><td>Dextrose</td><td>Fisher Chemicals</td><td>D16-1</td><td></td></tr><tr><td>EDTA (Ethylenediaminetetraacetic Acid)</td><td>Fisher Bioreagents</td><td>BP2482-500</td><td></td></tr><tr><td>0.5 M Phosphate buffer pH 7.2</td><td>Alfa Aesar</td><td>AAJ63974AP</td><td></td></tr></tbody></table>

metabolic labeling and profiling of transfer rnas using macroarrays

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for protein synthesis by translating codons in mRNA into amino acid sequences. tRNAs were long considered as house-keeping molecules that lacked regulatory functions. However, a growing body of evidence indicates that cellular tRNA levels fluctuate in correspondence to varying conditions such as cell type, environment, and stress. The fluctuation of tRNA expression directly influences gene translation, favoring or repressing the expression of particular proteins. Ultimately comprehending the dynamic of protein synthesis requires the development of methods able to deliver high-quality tRNA profiles. The method that we present here is named SPOt, which stands for Streamlined Platform for Observing tRNA. SPOt consists of three steps starting with metabolic labeling of cell cultures with radioactive orthophosphate, followed by guanidinium thiocyanate-phenol-chloroform extraction of radioactive total RNAs and finally hybridization on in-house printed macroarrays. tRNA levels are estimated by quantifying the radioactivity intensities at each probe spot. In the protocol presented here we profile tRNAs in Mycobacterium smegmatis mc2155, a nonpathogenic bacterium often used as a model organism to study tuberculosis.

Three independent biological replicates show that, under the tested growth conditions, all M. smegmatis tRNAs are expressed above background level (Figure 1). In this particular experiment, the observed standard deviation for each probe is comprised between 2% (Arg (TCT)) and 22% (Cys (GCA)) with a median at 5% (Figure 1). False changes between replicates are significantly influenced by factors such as array preparation and hybridization. High reproducibility is achieved through careful and consistent array printing as well as automated sample hybridization. There is a 5-fold difference between tRNA Ile (GAT) and tRNA (Val (TAC), the highest and lowest abundant species respectively. SPOt shows that the expression of tRNA isoacceptors is not uniform. Isoacceptors are species that hold the same amino acid but display different anticodon sequences and therefore decode different codons on mRNAs. For example, all Alanine isoacceptors are expressed at similar levels, whereas the highest and lowest Arginine accepting tRNAs differ by 3-fold.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56898/56898fig1.jpg" /> 
Figure 1: Representative tRNA macroarray results. (A) Scanned bacterial, mouse and Human macroarrays. M. smegmatis arrays use only 43 probes instead of 48 for mouse and Human. As a consequence, the bacterial array displays 40 empty spots (probes are replicated eight times on each array) that blend with the background. Most of them are clustered in the upper left corner. (B) Histogram and heatmap representations of tRNA profiles in M. smegmatis under optimal growth conditions. Probe signals are the average of three independent experiments (including bacterial growth, metabolic labeling, extraction and array hybridization) and are expressed as per thousand values of total tRNAs. Standard deviations for the three replicates are indicated as error bars and shades of orange on the histogram and heatmap respectively. <a href="http://cloudflare.jove.com/files/ftp_upload/56898/56898fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays at JoVE.com

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

We describe an original transfer RNA analysis platform named SPOt (Streamlined Platform for Observing tRNA). SPOt simultaneously measures cellular levels of all tRNAs in biological samples, in only three steps, and in less than 24 hours.

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for ...

metabolic-labeling-and-profiling-of-transfer-rnas-using-macroarrays

Research

JoVE Journal

Genetics

5.8K Views.  College of Charleston. We describe an original transfer RNA analysis platform named SPOt (Streamlined Platform for Observing tRNA). SPOt simultaneously measures cellular levels of all tRNAs in biological samples, in only three steps, and in less than 24 hours.

Video: Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

High Throughput MicroRNA Profiling: Optimized Multiplex qRT-PCR at Nanoliter Scale on the Fluidigm Dynamic ArrayTM IFCs

The broad involvement of miRNAs in critical processes underlying development, tissue homoeostasis and disease has led to a surging interest among the research and pharmaceutical communities. To study miRNAs, it is essential that the quantification of microRNA levels is accurate and robust. By comparing wild-type to small RNA deficient mouse embryonic stem cells (mESC), we revealed a lack of accuracy and robustness in previous published multiplex qRT-PCR techniques. Here, we describe an optimized method, including purifying away excessive primers from previous multiplex steps before singleplex real time detection, which dramatically increases the accuracy and robustness of the technique. Furthermore, we explain how performing the technique on a microfluidic chip at nanoliter volumes significantly reduces reagent costs and permits time effective high throughput miRNA expression profiling.

Here we describe an optimized multiplex reverse transcriptase quantitative PCR (qRT-PCR) protocol in combination with a microfluidic platform as a cost and time effective high-throughput screening tool for microRNA (miRNA) expression levels, especially when working with limited amounts of sample.

The broad involvement of miRNAs in critical processes underlying development, tissue homoeostasis and disease has led to a surging interest among the ...

Bioengineering

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for example, during cellular differentiation, morphogenesis, and functional stimulation (such as activation of immune cells), or after exposure to drugs and other factors from the local environment. Depending on the stimulus and cell type, these changes occur rapidly and at any possible level of gene regulation. Displaying all molecular processes of a responding cell to a certain type of stimulus/drug is one of the hardest tasks in molecular biology. Here, we describe a protocol that enables the simultaneous analysis of multiple layers of gene regulation. We compare, in particular, transcription factor binding (Chromatin-immunoprecipitation-sequencing (ChIP-seq)), de novo transcription (4-thiouridine-sequencing (4sU-seq)), mRNA processing, and turnover as well as translation (ribosome profiling). By combining these methods, it is possible to display a detailed and genome-wide course of action.
Sequencing newly transcribed RNA is especially recommended when analyzing rapidly adapting or changing systems, since this depicts the transcriptional activity of all genes during the time of 4sU exposure (irrespective of whether they are up- or downregulated). The combinatorial use of total RNA-seq and ribosome profiling additionally allows the calculation of RNA turnover and translation rates. Bioinformatic analysis of high-throughput sequencing results allows for many means for analysis and interpretation of the data. The generated data also enables tracking co-transcriptional and alternative splicing, just to mention a few possible outcomes.
The combined approach described here can be applied for different model organisms or cell types, including primary cells. Furthermore, we provide detailed protocols for each method used, including quality controls, and discuss potential problems and pitfalls.

This protocol describes the combinatorial use of ChIP-seq, 4sU-seq, total RNA-seq, and ribosome profiling for cell lines and primary cells. It enables tracking changes in transcription-factor binding, de novo transcription, RNA processing, turnover and translation over time, and displaying the overall course of events in activated and/or rapidly changing cells.

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for ...

Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity

Global defects in RNA polymerase II transcription might be overlooked by transcriptomic studies analyzing steady-state RNA. Indeed, the global decrease in mRNA synthesis has been shown to be compensated by a simultaneous decrease in mRNA degradation to restore normal steady-state levels. Hence, the genome-wide quantification of mRNA synthesis, independently from mRNA decay, is the best direct reflection of RNA polymerase II transcriptional activity. Here, we discuss a method using non-perturbing metabolic labeling of nascent RNAs in Saccharomyces cerevisiae (S. cerevisiae). Specifically, the cells are cultured for 6 min with a uracil analog, 4-thiouracil, and the labeled newly transcribed RNAs are purified and quantified to determine the synthesis rates of all individual mRNA. Moreover, using labeled Schizosaccharomyces pombe cells as internal standard allows comparing mRNA synthesis in different S. cerevisiae strains. Using this protocol and fitting the data with a dynamic kinetic model, the corresponding mRNA decay rates can be determined.

Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity

The protocol described here is based on the genome-wide quantification of newly synthesized mRNA purified from yeast cells labeled with 4-thiouracil. This method allows to measure mRNA synthesis uncoupled from mRNA decay and, thus, provides an accurate measurement of RNA polymerase II transcription.

Global defects in RNA polymerase II transcription might be overlooked by transcriptomic studies analyzing steady-state RNA. Indeed, the global decrease in ...

Extremely Rapid and Specific Metabolic Labelling of RNA In Vivo with 4-Thiouracil (Ers4tU)

The nucleotide analogue, 4-thiouracil (4tU), is readily taken up by cells and incorporated into RNA as it is transcribed in vivo, allowing isolation of the RNA produced during a brief period of labelling. This is done by attaching a biotin moiety to the incorporated thio group and affinity purifying, using streptavidin coated beads. Achieving a good yield of pure, newly synthesized RNA that is free of pre-existing RNA makes shorter labelling times possible and permits increased temporal resolution in kinetic studies. This is a protocol for very specific, high yield purification of newly synthesized RNA. The protocol presented here describes how RNA is extracted from the yeast Saccharomyces cerevisiae. However, the protocol for purification of thiolated RNA from total RNA should be effective using RNA from any organism once it has been extracted from the cells. The purified RNA is suitable for analysis by many widely used techniques, such as reverse transcriptase-qPCR, RNA-seq and SLAM-seq. The specificity, sensitivity and flexibility of this technique allow unparalleled insights into RNA metabolism.

Extremely Rapid and Specific Metabolic Labelling of RNA In Vivo with 4-Thiouracil Ers4tU

The use of thiolated uracil to sensitively and specifically purify newly transcribed RNA from the yeast Saccharomyces cerevisiae.

The nucleotide analogue, 4-thiouracil (4tU), is readily taken up by cells and incorporated into RNA as it is transcribed in vivo, allowing isolation of ...

Biochemistry

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells

Estrogen plays vital roles in mammary gland development and breast cancer progression. It mediates its function by binding to and activating the estrogen receptors (ERs), ER&#945;, and ER&#946;. ER&#945; is frequently upregulated in breast cancer and drives the proliferation of breast cancer cells. The ERs function as transcription factors and regulate gene expression. Whereas ER&#945;&#39;s regulation of protein-coding genes is well established, its regulation of noncoding microRNA (miRNA) is less explored. miRNAs play a major role in the post-transcriptional regulation of genes, inhibiting their translation or degrading their mRNA. miRNAs can function as oncogenes or tumor suppressors&#160;and are also promising biomarkers. Among the miRNA assays available, microarray and quantitative real-time polymerase chain reaction (qPCR) have been extensively used to detect and quantify miRNA levels. To identify miRNAs regulated by estrogen signaling in breast cancer, their expression in ER&#945;-positive breast cancer cell lines were compared before and after estrogen-activation using both the &#181;Paraflo-microfluidic microarrays and Dual Labeled Probes-low density arrays. Results were validated using specific qPCR assays, applying both Cyanine dye-based and Dual Labeled Probes-based chemistry. Furthermore, a time-point assay was used to identify regulations over time. Advantages of the miRNA assay approach used in this study is that it enables a fast screening of mature miRNA regulations in numerous samples, even with limited sample amounts. The layout, including the specific conditions for cell culture and estrogen treatment, biological and technical replicates, and large-scale screening followed by in-depth confirmations using separate techniques, ensures a robust detection of miRNA regulations,&#160;and eliminates false positives and other artifacts. However, mutated or unknown miRNAs, or regulations at the primary and precursor transcript level, will not be detected. The method presented here represents a thorough investigation of estrogen-mediated miRNA regulation.

Molecular signaling through both estrogen and microRNAs are critical in breast cancer development and growth. Estrogen activates the estrogen receptors, which are transcription factors. Many transcription factors can regulate the expression of microRNAs, and estrogen-regulated microRNAs can be profiled using different large-scale techniques.

Estrogen plays vital roles in mammary gland development and breast cancer progression. It mediates its function by binding to and activating the estrogen ...

Medicine

A Rapid High-throughput Method for Mapping Ribonucleoproteins (RNPs) on Human pre-mRNA

Sequencing RNAs that co-immunoprecipitate (co-IP) with RNA binding proteins has increased our understanding of splicing by demonstrating that binding location often influences function of a splicing factor.  However, as with any sampling strategy the chance of identifying an RNA bound to a splicing factor is proportional to its cellular abundance.  We have developed a novel in vitro approach for surveying binding specificity on otherwise transient pre-mRNA. This approach utilizes a specifically designed oligonucleotide pool that tiles across introns, exons, splice junctions, or other pre-mRNA.  The pool is subjected to some kind of molecular selection. Here, we demonstrate the method by separating the oligonucleotide into a bound and unbound fraction and utilize a two color array strategy to record the enrichment of each oligonucleotide in the bound fraction. The array data generates high-resolution maps with the ability to identify sequence-specific and structural determinates of ribonucleoprotein (RNP) binding on pre-mRNA.  A unique advantage to this method is its ability to avoid the sampling bias towards mRNA associated with current IP and SELEX techniques, as the pool is specifically designed and synthesized from pre-mRNA sequence. The flexibility of the oligonucleotide pool is another advantage since the experimenter chooses which regions to study and tile across, tailoring the pool to their individual needs.  Using this technique, one can assay the effects of polymorphisms or mutations on binding on a large scale or clone the library into a functional splicing reporter and identify oligonucleotides that are enriched in the included fraction.  This novel in vitro high-resolution mapping scheme provides a unique way to study RNP interactions with transient pre-mRNA species, whose low abundance makes them difficult to study with current in vivo techniques.  



A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

Due to the transient nature of pre-mRNA, it can be difficult to isolate and study in vivo. Here, we present a novel in vitro approach to investigate RNA-protein interactions using a synthetic oligo pool that tiles across selected regions of pre-mRNA.

Sequencing RNAs that co-immunoprecipitate (co-IP) with RNA binding proteins has increased our understanding of splicing by demonstrating that binding ...

Biology

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays

Quantitative real-time PCR (QPCR) has emerged as an accurate and valuable tool in profiling gene expression levels.  One of its many advantages is a lower detection limit compared to other methods of gene expression profiling while using smaller amounts of input for each assay.  Automated qPCR setup has improved this field by allowing for greater reproducibility.  Its convenient and rapid setup allows for high-throughput experiments, enabling the profiling of many different genes simultaneously in each experiment.  This method along with internal plate controls also reduces experimental variables common to other techniques.  
We recently developed a qPCR assay for profiling of pre-microRNAs  (pre-miRNAs) using a set of 186 primer pairs.  MicroRNAs have emerged as a novel class of small, non-coding RNAs with the ability to regulate many mRNA targets at the post-transcriptional level.  These small RNAs are first transcribed by RNA polymerase II as a primary miRNA (pri-miRNA) transcript, which is then cleaved into the precursor miRNA (pre-miRNA).  Pre-miRNAs are exported to the cytoplasm where Dicer cleaves the hairpin loop to yield mature miRNAs.  Increases in miRNA levels can be observed at both the precursor and mature miRNA levels and profiling of both of these forms can be useful.  There are several commercially available assays for mature miRNAs; however, their high cost may deter researchers from this profiling technique.  Here, we discuss a cost-effective, reliable, SYBR-based qPCR method of profiling pre-miRNAs.  Changes in pre-miRNA levels often reflect mature miRNA changes and can be a useful indicator of mature miRNA expression.  However, simultaneous profiling of both pre-miRNAs and mature miRNAs may be optimal as they can contribute nonredundant information and provide insight into microRNA processing.  Furthermore, the technique described here can be expanded to encompass the profiling of other library sets for specific pathways or pathogens.

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR qPCR Arrays

We will demonstrate the setup and analysis of pre-microRNA 96-well arrays for QPCR using a robot as well as by hand with a Thermo Scientific Matrix multichannel pipette.

Quantitative real-time PCR (QPCR) has emerged as an accurate and valuable tool in profiling gene expression levels.  One of its many advantages is a lower ...

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene expression. Along with a better understanding of the involved molecular mechanisms, precise measurements of the underlying kinetics have become increasingly important. Here, these powerful methodologies face major limitations due to intrinsic properties of the template samples they study, i.e. total cellular RNA. In many cases changes in total cellular RNA occur either too slowly or too quickly to represent the underlying molecular events and their kinetics with sufficient resolution. In addition, the contribution of alterations in RNA synthesis, processing, and decay are not readily differentiated.
We recently developed high-resolution gene expression profiling to overcome these limitations. Our approach is based on metabolic labeling of newly transcribed RNA with 4-thiouridine (thus also referred to as 4sU-tagging) followed by rigorous purification of newly transcribed RNA using thiol-specific biotinylation and streptavidin-coated magnetic beads. It is applicable to a broad range of organisms including vertebrates, Drosophila, and yeast. We successfully applied 4sU-tagging to study real-time kinetics of transcription factor activities, provide precise measurements of RNA half-lives, and obtain novel insights into the kinetics of RNA processing. Finally, computational modeling can be employed to generate an integrated, comprehensive analysis of the underlying molecular mechanisms.

Total cellular RNA provides a poor template for studying short-term changes in RNA synthesis and decay as well as the kinetics of RNA processing. Here, we describe metabolic labeling of newly transcribed RNA with 4-thiouridine followed by thiol-specific biotinylation and purification of newly transcribed RNA allowing to overcome these limitations.

The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene ...

Assessment of Selective mRNA Translation in Mammalian Cells by Polysome Profiling

Regulation of protein synthesis represents a key control point in cellular response to stress. In particular, discreet RNA regulatory elements were shown to allow to selective translation of specific mRNAs, which typically encode for proteins required for a particular stress response. Identification of these mRNAs, as well as the characterization of regulatory mechanisms responsible for selective translation has been at the forefront of molecular biology for some time. Polysome profiling is a cornerstone method in these studies. The goal of polysome profiling is to capture mRNA translation by immobilizing actively translating ribosomes on different transcripts and separate the resulting polyribosomes by ultracentrifugation on a sucrose gradient, thus allowing for a distinction between highly translated transcripts and poorly translated ones. These can then be further characterized by traditional biochemical and molecular biology methods. Importantly, combining polysome profiling with high throughput genomic approaches allows for a large scale analysis of translational regulation.

The ability of cells to adapt to stress is crucial for their survival. Regulation of mRNA translation is one such adaptation strategy, providing for rapid regulation of the proteome. Here, we provide a standardized polysome profiling protocol to identify specific mRNAs that are selectively translated under stress conditions.

Regulation of protein synthesis represents a key control point in cellular response to stress. In particular, discreet RNA regulatory elements were shown ...

Expression Profiling with Microarrays

Microarrays are important tools for profiling gene expression, and are based on complementary binding between probes that are attached to glass chips and nucleic acids derived from samples. Using these arrays, scientists can simultaneously evaluate the expression of thousands of genes. In addition, the expression profiles of different cells or tissue types can be compared, allowing researchers to deduce how the expression of different genes change during biological processes, and thus gain insight into how the genes may function in pathways or networks.Here, JoVE explains the principles behind microarrays. This is followed by a general protocol for performing a microarray experiment, and a brief introduction to analyzing microarray data. We end on a discussion of how scientists are currently using microarrays, for example to compare gene expression between different cell types derived from cancerous and non-cancerous tissues, to study important biological problems.

Microarrays are important tools for profiling gene expression, and are based on complementary binding between probes that are attached to glass chips and ...

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Podsumowanie

Przeglądaj więcej filmów

Rozdziały w tym wideo

High Throughput MicroRNA Profiling: Optimized Multiplex qRT-PCR at Nanoliter Scale on the Fluidigm Dynamic ArrayTM IFCs

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity

Extremely Rapid and Specific Metabolic Labelling of RNA In Vivo with 4-Thiouracil (Ers4tU)

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells

A Rapid High-throughput Method for Mapping Ribonucleoproteins (RNPs) on Human pre-mRNA

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

Assessment of Selective mRNA Translation in Mammalian Cells by Polysome Profiling

Expression Profiling with Microarrays