RNA-seq has the power to reveal the mRNAs that are produced in a given cell, but it does not provide any information about the transcripts that are actually translated into proteins. However, a recently developed technique known as ribosome profiling can be used to map the genome-wide distribution of ribosomes along mRNAs, thereby identifying those that are actively translated1. The mRNA fragments, known as 'footprints', that are covered by the ribosome are protected from nuclease digestion and can be isolated and sequenced, to reveal the 'translatome' of the cell of interest.

Credit: NPG

This technique has previously been applied to several model systems, including Escherichia coli, yeast and mouse cells. Vasquez et al.2 are the first to apply the method to a parasitic pathogen by examining in vitro cultures of Trypanosoma brucei — the causative agent of sleeping sickness in humans. T. brucei is a particularly interesting organism to study using this technique as the parasite exhibits little control of gene expression at the transcriptional level, which suggests that it is probably heavily dependent on mechanisms that regulate transcript stability, the rate of translation and protein turnover. Previous studies of T. brucei applied polysome profiling3,4 to identify mRNA transcripts that are associated with polysomes. Ribosome profiling is complementary to these studies, as it identifies those transcripts that are actually translated and it also enables the rate of translation to be measured by estimating the density of footprints along a transcript.

T. brucei has a complex life cycle, in which it moves between mammalian hosts by means of the tsetse fly vector. Vasquez et al.2 investigated the procyclic form of T. brucei, which is found in the vector, and the blood-stage form, which is present in the mammalian host. Owing to the differences that these two environments present, including lower temperature and reduced availability of glucose in the vector, the gene-expression profile of the two parasite stages will differ. Thus, for each developmental stage, a library of ribosomal footprints and a control mRNA library was generated.

Ribosome footprints along the transcripts showed a strong three-nucleotide pattern of periodicity, which reflects the translation of codons. Thus, the authors were able to identify previously unannotated putative coding sequences (CDSs), more than 200 of which seem to be important for parasite fitness (particularly the blood-stage form), as indicated by a re-evaluation of existing proteomics and genome-wide RNA interference data5.

In total, the translation of 8,072 genes (82% of annotated CDSs) was detected, using a threshold of >10 ribosome footprint reads per CDS. However, the rate of translation, which was calculated by dividing the number of ribosomal footprint reads by the number of mRNA reads, differed substantially between individual genes. A 117-fold range in translational efficiency was observed for the procyclic form and a 64-fold range was observed for the blood-stage form. The authors used the rank order of translational efficiencies to compare the two life stages, as a direct comparison assumes that the rate of translation is the same in both life stages, which is probably not the case, given the difference in temperature. Overall, a positive correlation in translation efficiency was observed; however, stage-specific differences for a subset of genes were also detected, some of which were linked to glucose metabolism and the regulation of translation.

Regulatory elements, including small upstream ORFs (uORFs) that are located in the 5′ UTR of mRNAs, have been shown to negatively regulate translation. This study identified uORFs in 22% of T. brucei 5′ UTRs, and their presence correlated with reduced translational efficiency. Although this analysis was complicated by the presence of multiple 5′ UTR isoforms, it does suggest that uORFs have an important regulatory role in T. brucei.

This study reveals many features of T. brucei translation using a single genome-wide assay. By applying this technique to a broader range of pathogens, it has the potential to identify many more new CDSs — CDSs that are 'found in translation'.