In order to identify genes that affect protein synthesis, we screened the entire set of yGDA (~4700) for increased sensitivity to the aminoglycoside paromomycin. Paromomycin binds to the small ribosomal subunit of eukaryotic cells and compromises the translation fidelity 17. Previously, it was shown that deletion of certain translation related genes caused increased sensitivity to paromomycin 1819. Therefore, we employed hypersensitivity to this drug as a way to detect novel gene candidates involved in translation. It should be noted that the deletion of certain translation related genes would cause increased resistance to paromomycin. This however, has not been investigated in our analysis.

We used yeast colony size reduction (CSR) as a tool to detect sensitivity to drug treatments. We have previously shown, that based on the parameters used by us (see Materials and Methods), CSR analysis can detect approximately 63% of the sensitive strains that are detected by a large-scale spot test (ST) analysis with no repeats 20. Hence, there are a number of sensitive strains that would be missed by our analysis, that might otherwise be detected by ST. Similarly, the same large-scale ST analysis failed to detect 59% of the strains detected by CSR, which may represent novel/false-positives associated with CSR.

Here, we use sensitivity to paromomycin as a tool to detect protein synthesis related genes. A draw back for this, as well as other similar drug-based screening tests, is the detection of sensitive strains for those genes with no direct relation to the activity of the target drugs. A major source of such false-positives in our experiments may stem from those genes that play a role in general stress conditions. Multi-drug resistant genes represent some of these examples. For instance, it has been shown that the deletion of QDR1, a transporter gene and a member of efflux pumps, confers sensitivity to several unrelated drugs 21. To increase the specificity of our selection procedure, we coupled our initial screen with a secondary search (based on the same parameters) for increased sensitivity to a second drug, which has no reported activity on the process of translation. For this purpose, we selected calcofluor white (CW), which is known to inhibit cell wall function by binding with chitin 22. In this way, only those gene deletions that conferred sensitivity to paromomycin alone may represent meaningful positives.

As expected, our large-scale approach identified numerous translation genes such as TEF4 (translation elongation factor EF-1 gamma), HCR1 (a component of translation initiation factor 3), RPS18B (a ribosomal protein of small subunit), etc, which are sensitive to paromomycin and not to CW. The complete list of these genes is found in Additional file 1. The list of the genes that were sensitive to both paromomycin and CW is found in Additional file 2. Of the 325 gene deletions sensitive to paromomycin alone, we found 42 genes that often appeared in our similar drug screenings using different bioactive compounds. These may represent false-positives and should be treated with caution. From the 325 total reported genes, 134 have been previously linked to the overall process of protein biosynthesis. 191 of them however, have never been connected in any way to this process, and therefore, may also represent novel/false-positive genes. These genes can be further classified into 5 smaller categories based on the cellular processes in which they participate, plus those which are unknown. As indicated in Figure 1, the minor categories are: metabolism with 45 genes, cellular component biogenesis and organization with 28, DNA maintenance with 21, transport with 20 and others with 38 genes. There were also 39 genes, which are unknown. An explanation for these smaller categories is that they may represent minor cellular target sites (side-effects) for paromomycin. Alternatively, they may simply represent false-positives (see above). It is also possible that some of these genes might have novel roles during translation. In this case, they may represent communication bridges between different cellular processes and protein synthesis.

One of the previously uncharacterized ORF identified in this screen is YBR261C. There is no reported information about this ORF, except that it is computationally predicted to have a methyltransferases domain 23. We therefore hypothesized that this might be a novel translation related gene. We termed this ORF, TAE1, for Translation Associated Element 1, and subjected it to further analysis for its potential involvement in protein synthesis. ST analysis was used to confirm our large-scale observations (Figure 2). When the growth media was supplemented with a sub-inhibitory concentration of paromomycin (13 mg/ml), a deletion strain for TAE1 (tae1Δ) showed a reduction in its growth pattern (Figure 2).

We then examined tae1Δ strain for its increased sensitivity to 3-amino-1,2,4-triazole (3-AT) and cycloheximide. 3-AT can affect translation by altering the pool of amino acids in the cell 24. Cycloheximide binds to large ribosomal subunit 25, and inhibits translation elongation by interfering with tRNA translocation 26. It has previously been reported that deletion of certain genes that affect translation may confer sensitivity to multiple drugs that target translation. For example, deletion of Sfp1, which regulates ribosome biogenesis, confers increased sensitivity to both cycloheximide and paromomycin 27. Shown in Figure 2, our spot test analysis indicated that in addition to paromomycin, tae1Δ also showed increased sensitivity to 3-AT. Also some sensitivity for tae1Δ to cycloheximide was occasionally observed. However, due to irreproducibility of these observations, this sensitivity was presumed to be an artifact.

During the preparation of this manuscript, a new study was reported in which sensitivity of yeast gene deletion mutants to paromomycin were investigated using a heterozygous diploid yeast gene deletion mutant array 28. This system is different from ours (haploid based), as its diploid mutant strains always carry a copy of the wild type genes and consequently show less obvious growth defects 29. Of the 51 mutant strains that were identified by the authors as sensitive to paromomycin, 39 are shared between the two systems. Of these, 16 mutants were also identified by our haploid system. It is worth mentioning that tae1Δ was not detected to have increased sensitivity to paromomycin in the heterozygous system, further highlighting the difference between the two systems 28.

Translation genes can be involved in different aspects of translation. To examine the involvement of novel genes in protein synthesis, we divided translation into three general categories. Group one includes those genes that are associated with ribosome biogenesis, group two contains genes that alter translation efficiency, and group three is composed of the genes that affect translation fidelity. Depending on their molecular function(s), some translation genes may fall into none 30, one 2731 or more 32 of these three categories. If TAE1 is involved in the process of translation, it might fall into one or more of these categories.

Ribosome biogenesis and assembly is one of the most important processes in the protein synthesis pathway 33. This process might be explained as the overall step that leads to the formation and assembly of functional ribosomes and includes regulation of pre-rRNA transcription, and its corresponding mechanisms, pre-rRNA processing, rRNA transport, rRNA maturation, ribosome assembly, etc. 34. We therefore reasoned that depending on the molecular function(s) of TAE1, if this gene is involved in ribosome biogenesis or assembly, its deletion might result in the alteration of the profile of ribosomal subunits. To examine this possibility, ribosome profile analysis was performed. As expected, distinct 40S and 60S subunit peaks, as well as 80S monosomes and polysome peaks (Figure 3) were detected in both the wild type and tae1Δ strains. In addition, tae1Δ strain showed a reduction in polysomes and corresponding increases in 80S monosomes and 60S subunits (Figure 3). These alterations in ribosomal profile further indicate the involvement of TAE1 in protein synthesis.

If TAE1 is involved in protein synthesis, then based on its molecular function(s), its deletion may alter the cell's efficiency s to synthesize proteins. To investigate this possibility, we used [³⁵S] methionine incorporations to measure the rate of total protein synthesis in different strains. As indicated in Figure 4A, it was observed that on average, tae1Δ had a reduced level of [³⁵S] methionine incorporation (approximately 22%) compared to the control strain. To confirm this observation, we used an inducible β-galactosidase reporter construct (Figure 4B). It was observed that the deletion of TAE1 reduced the level of β-galactosidase synthesis from an inducible expression plasmid by approximately ten-folds (Figure 4B). These observations suggest that deletion of TAE1 may reduce the efficiency of protein synthesis in a cell, and provide further support that TAE1 affects protein synthesis.

To make a functional protein, the fidelity of protein synthesis is maintained at almost all stages of translation. This fidelity is controlled during the start site selection and elongation when the mis-incorporation of the wrong amino acid may alter the integrity of the final product, as well as during termination, when a stop codon might be read through. If TAE1 is involved in translation, then it might be expected that based on its molecular function(s), the deletion of this gene may alter the fidelity of translation. Translation fidelity can be studied using specialized expression systems such as those that contain β-galactosidase expression cassettes, with premature stop codons 35. In this investigation, we used plasmids pUKC817 and pUKC818 that contain lacZ genes carrying the nonsense codons UAA and UAG, respectively 35. It was observed that the deletion of TAE1 resulted in an increased level of read through for the nonsense codons investigated, suggesting that in this deletion strain, the translation fidelity seem to be compromised (Figure 5A). For unknown reasons, the average values for β-galactosidase activities in the wild type strain, were systematically higher than expected.

Since differential levels of β-galactosidase activity in above experiments may also stem from altered levels of mRNAs, the content of β-galactosidase mRNAs of WT and tae1Δ were investigated using Q-RT-PCR. We observed no significant variation in the amounts of these mRNAs (Figure 5B), which could explain the observed difference for the β-galactosidase activities. It was therefore concluded that the observed differences likely stem from translation read through. Altogether, the results indicate that the deletion of TAE1 seems to compromise translation fidelity, providing further evidence that TAE1 affects translation.

The genes that are functionally related and are involved in similar pathways, often genetically interact with each other. Consequently, studying the genetic interactions of a novel gene is often used as a method to infer the function of that gene 3637. If TAE1 is a true translation gene, then it might be expected that TAE1 would genetically interact with certain known translation associated genes. To investigate this possibility, we examined the genetic interactions of TAE1 with a set of 384 genes, which are known or thought to be involved in translation. As indicated in Figure 6, it was observed that TAE1 genetically interacted with numerous translation related genes to produce sick phenotypes, which are classified as i) very sick, ii) sick, and iii) moderate. Lethal interactions were not considered. The interactions between TAE1 and translation related genes were further divided into three categories with ribosomal proteins forming the largest cluster (16 genes), followed by those involved in amino acids and protein production (7 genes), and those involved in rRNA synthesis (2 genes). Descriptions of these genes are listed in Additional file 3. The fact that TAE1 genetically interacts with different translation associated genes provides further evidence for the involvement of TAE1 in the process of translation.

To examine the cellular activity of Tae1 protein, we employed a high throughput approach, based on the phenotypic suppression of the gene deletion mutants that have known functions. Deletion of genes, which are involved in a specific pathway, may cause increased sensitivity to treatments that target the same process. Such hypersensitivities can be compensated by the overexpression of other genes with similar cellular functions. For example, it has previously been reported that the absence of Yku80, involved in telomere maintenance, causes increased sensitivity to elevated temperature. Overexpression of either Est2, a catalytic subunit of telomerase, or Tlc1, the RNA template component of telomerase, compensated for the absence of Yku80 and reversed the heat hypersensitivity of yku80Δ 38.

Here, we investigated the activity of Tae1 protein by examining the effect of its overexpression in suppressing hypersensitivities to antibiotics neomycin and streptomycin for the above 384 translation related gene deletion yeast strains. Like paromomycin, the antibiotics neomycin and streptomycin, belong to the aminoglycoside family, which binds to ribosomes and disrupts translation 30. We observed that overexpression of Tae1 protein, suppressed the drug sensitivity phenotypes for 28 deletion mutants of known translation genes (Figure 7). These 28 mutants showed sensitivity to treatment with neomycin and/or streptomycin. Tae1 overexpression however, reversed the observed drug sensitivities. These 28 gene deletion mutants can be categorized into two main groups of gene deletions for ribosomal proteins (17 genes), and those for translation control proteins (8 genes). Descriptions of the deleted genes are listed in Additional file 4. The fact that overexpression of Tae1 suppresses the phenotypes of deletion mutants for translation genes, further confirms an involvement for TAE1 in protein synthesis.

Sub-inhibitory concentrations of drugs were estimated from minimum inhibitory concentration (MIC) measurements based on a 96 varied concentration format as described in 41.

Approximately 4700 MATa haploid yeast, S. cerevisiae strains (BY4741, MATa ura3Δ0 leu2Δ0 his3Δ1 met15Δ0) from the non-essential Gene Deletion Array (yGDA) described in 35 was manually arrayed onto agar plates as previously described 36 in a 384 array format, with sub-inhibitory concentrations of paromomycin (13 mg/ml), CW (40 μg/ml) or without a drug (control). All plates were incubated at 30°C for 1–2 days. The sensitivity of the gene deletion array to different drugs was investigated as before 36. In brief, different strains are pinned on two plates, one with a sub-inhibitory concentration of a target drug and one without (used as a control) and incubated at 30°C for 1–2 days. Digital images of plates were used to analyze the growth of individual colonies. For every plate the average size of colonies (white pixels) was calculated from equation (1).

S a v e = 1 / N ∑ i = 1 N S i MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xI8qiVKYPFjYdHaVhbbf9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaem4uam1aaSbaaSqaaiabdggaHjabdAha2jabdwgaLbqabaGccqGH9aqpcqaIXaqmcqGGVaWlcqWGobGtdaaeWaqaaiabdofatnaaBaaaleaacqWGPbqAaeqaaaqaaiabdMgaPjabg2da9iabigdaXaqaaiabd6eaobqdcqGHris5aaaa@3EBF@

where N is the total number of colonies present in a given plate and S_i is the area of object i. The deviation of area for each colony from the plate's average area was used for further analysis (relative growth) and was calculated by subtracting the scalar S_ave from the plate's ordered area array explained in equation (2).

ΔS_i = S_i - S_ave; i = 1, ..., 384 (16 × 24 = 384)

Relative colony size reduction of more than 30% was counted as a "hit". Each experiment was repeated three times. The gene deletion strains, which were "hits" in two or more of the three experiments, were counted as positives. Colonies with the highest two average reductions of 61% or more and 30–60% were defined supersensitives and sensitives, respectively.

ST test analysis was performed by growing yeast cell cultures in YEPD media to mid-log, following 10-3 to 10-6 folds dilutions. Twenty microliters of each dilution (gradually decreasing), was then spotted onto media containing the sub-inhibitory concentrations of the drugs (13 mg/ml paromomycin, 22 mg/ml 3-AT, and 45 ng/ml cycloheximide), and without (control). YEPD media was used for cycloheximide and SC media was used for paromomycin and 3-AT plates. The growth patterns were compared after 1–2 days at 30°C as in 42.

Constitutively expressed β-galactosidase (using pUKC815, pUKC817 and pUKC818) was assayed as described 43. The units of enzyme activity were calculated as nanomoles of O-nitrophenyl-α-D-galactopyranoside (OPNG) hydrolyzed per microgram of total protein 44. All assays were conducted in triplicate. Induced β-galactosidase (using p416) was assayed as before 45.

In vivo [³⁵S] methionine incorporation was performed as previously described by Schwartz and Parker 46 with modifications. Briefly, yeast strains were grown to mid-log phase at 30°C in YEPD. The cells were harvested, resuspended in pre-warmed minimal medium lacking methionine, and supplemented with 10 μCi/ml of [³⁵S] methionine. The cells were incubated for 1 h at 30°C and harvested by centrifugation. The samples were then washed with distilled water six times and collected (1 μl aliquot) on Whatman paper. The paper was air dried and exposed to storage phosphor screen for 1 h. The counts were normalized to the final cell totals. Each experiment was repeated at least four times.

Total RNA was isolated using Bio-Rad RNA isolation kit. cDNA was constructed from 0.5 μg of total RNA of each strain using iScript cDNA synthesis kit with SYBR green supermix (Bio-Rad) according to the instructions of the manufacturer. The quantification of mRNA was performed using real-time RT-PCR (Q-RT-PCR) on a Rotor-Gene RG-300 from Corbett research. The PCR quantification and melting curves were generated using the Rotor gene 6 software. The amplification was performed: initial denaturation 95°C for 10 min followed by 40 cycles at 95°C for 30 s, 55°C for 20 s and 72°C for 20 s each with using 50 nmoles each of the forward (5'-ACTATCCCGACCGCCTTACT) and reverse (5'-TAGCGGCTGATGTTGAACTG) primers. The fluorescence was read at the end of each round of amplification. All standard dilutions and samples were run in triplicate. Quantification of mRNA were achieved by comparing the threshold cycle (C_t) value of the sample RNA from deletion strain with the C_t value of WT strain's standard RNA 47.

Ribosome profiling was performed as described by Foani et al 48 with the following modifications. Wild type and mutant yeast cells were grown in YEPD at 30°C to a density of 2 × 10⁷ cells/ml. Cycloheximide (50 μg/ml) was added to each culture and the cultures were quickly chilled in ice water bath. Cells were then centrifuged at 4000 rpm for 4 min at 4°C by sorvall SLA-1500 rotor. Cell pellets were resuspended in 10 ml of ice-cold YA buffer (breaking buffer A: 10 mM Tris-HCl [pH 7.4], 100 mM NaCl, 30 mM MgCl₂, cycloheximide 50 μg/ml, heparin 200 μg/ml) and centrifuged 4000 rpm, 4 min, at 4°C (Sorvall SS34 rotor), twice. The pellets were then resuspended in 0.5 ml of YA buffer by vortex and stored at -80°C till the next day. Cells were then thawed on ice water bath. Glass beads were added and vortex for 20 sec at maximum speed, 10 times with 30 sec interval. The supernatants were centrifuged at 8,000 × g and 10,000 × g for 10 min and 30 min, respectively. Twenty OD₂₆₀ units of each supernatant were fractionated on 8–48% sucrose gradients containing 50 mM Tris-acetate (pH 7.0), 50 mM NH₄Cl, 12 mM MgCl₂, and 1 mM dithiothreitol. The extracts were then centrifuged for 2.5 hrs at 39,000 rpm using a SW40-Ti rotor in a Beckman LE-80K at 4°C. The ribosome profiles were analyzed from the collected gradient solutions by monitoring the absorbance at 254 nm. Each experiment was repeated three times with similar results.

Genetic interactions between TAE1 and a set of yeast gene deletion strains for 384 genes known or thought to be involved in translation were assessed by synthetic genetic miniarray profiling as discussed in 49 and the colony growth differences were assessed as in 20. Possible synthetic sick interactions were confirmed by a spotting assay explained in 50. We divided these interactions into strong, moderate and weak interactions based on their double mutant phenotypes of very sick, sick and slightly sick.

The TAE1 overexpression construct, pGAL1/10-GST-6xHis-YBR261C is obtained from the yeast gene overexpression array explained in 51. A compatible MATα strain (Y7092, MATα can1Δ::STE2pr-Sp_his5lyp1Δhis3Δ1 leu2Δ0 ura3Δ0 met15Δ0) is then transformed with this construct and was crossed with a set of yeast gene deletion strains for 384 translation genes (see above) as in 49. Sensitivity of yeast strains with or without TAE1 overexpression, against neomycin and streptomycin was performed using colony size measurements as discussed in 20. Phenotypic complementations were divided into two categories of complete and partial suppressions. Partial complementation against both drugs is assigned partial. Complete complementation against one drug, regardless of the other, is assigned complete.