For decades, identifying the regions of a bacterial chromosome that are necessary for viability has relied on mapping integration sites in libraries of random transposon mutants to find loci that are unable to sustain insertion. To date, these studies have analyzed subsaturated libraries, necessitating the application of statistical methods to estimate the likelihood that a gap in transposon coverage is the result of biological selection and not the stochasticity of insertion. As a result, the essentiality of many genomic features, particularly small ones, could not be reliably assessed. We sought to overcome this limitation by creating a completely saturated transposon library in Mycobacterium tuberculosis In assessing the composition of this highly saturated library by deep sequencing, we discovered that a previously unknown sequence bias of the Himar1 element rendered approximately 9% of potential TA dinucleotide insertion sites less permissible for insertion. We used a hidden Markov model of essentiality that accounted for this unanticipated bias, allowing us to confidently evaluate the essentiality of features that contained as few as 2 TA sites, including open reading frames (ORF), experimentally identified noncoding RNAs, methylation sites, and promoters. In addition, several essential regions that did not correspond to known features were identified, suggesting uncharacterized functions that are necessary for growth. This work provides an authoritative catalog of essential regions of the M. tuberculosis genome and a statistical framework for applying saturating mutagenesis to other bacteria. Importance Sequencing of transposon-insertion mutant libraries has become a widely used tool for probing the functions of genes under various conditions. The Himar1 transposon is generally believed to insert with equal probabilities at all TA dinucleotides, and therefore its absence in a mutant library is taken to indicate biological selection against the corresponding mutant. Through sequencing of a saturated Himar1 library, we found evidence that TA dinucleotides are not equally permissive for insertion. The insertion bias was observed in multiple prokaryotes and influences the statistical interpretation of transposon insertion (TnSeq) data and characterization of essential genomic regions. Using these insights, we analyzed a fully saturated TnSeq library for M. tuberculosis, enabling us to generate a comprehensive catalog of in vitro essentiality, including ORFs smaller than those found in any previous study, small (noncoding) RNAs (sRNAs), promoters, and other genomic features.

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Comprehensive Essentiality Analysis of the Mycobacterium tuberculosis Genome via Saturating Transposon Mutagenesis.

Traditional annotation of protein-encoding genes relied on assumptions, such as one open reading frame (ORF) encodes one protein and minimal lengths for translated proteins. With the serendipitous discoveries of translated ORFs encoded upstream and downstream of annotated ORFs, from alternative start sites nested within annotated ORFs and from RNAs previously considered noncoding, it is becoming clear that these initial assumptions are incorrect. The findings have led to the realization that genetic information is more densely coded and that the proteome is more complex than previously anticipated. As such, interest in the identification and characterization of the previously ignored 'dark proteome' is increasing, though we note that research in eukaryotes and bacteria has largely progressed in isolation. To bridge this gap and illustrate exciting findings emerging from studies of the dark proteome, we highlight recent advances in both eukaryotic and bacterial cells. We discuss progress in the detection of alternative ORFs as well as in the understanding of functions and the regulation of their expression and posit questions for future work.

Alternative ORFs and small ORFs: shedding light on the dark proteome.

The initiating nucleotide found at the 5’ end of primary transcripts has a distinctive triphosphorylated end that distinguishes these transcripts from all other RNA species. Recognizing this distinction is key to deconvoluting the primary transcriptome from the plethora of processed transcripts that confound analysis of the transcriptome. The currently available methods do not use targeted enrichment for the 5′end of primary transcripts, but rather attempt to deplete non-targeted RNA. We developed a method, Cappable-seq, for directly enriching for the 5' end of primary transcripts and enabling determination of transcription start sites at single base resolution. This is achieved by enzymatically modifying the 5′ triphosphorylated end of RNA with a selectable tag. We first applied Cappable-seq to E. coli, achieving up to 50 fold enrichment of primary transcripts and identifying an unprecedented 16539 transcription start sites (TSS) genome-wide at single base resolution. We also applied Cappable-seq to a mouse cecum sample and identified TSS in a microbiome. Cappable-seq allows for the first time the capture of the 5′ end of primary transcripts. This enables a unique robust TSS determination in bacteria and microbiomes.  In addition to and beyond TSS determination, Cappable-seq depletes ribosomal RNA and reduces the complexity of the transcriptome to a single quantifiable tag per transcript enabling digital profiling of gene expression in any microbiome.

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A novel enrichment strategy reveals unprecedented number of novel transcription start sites at single base resolution in a model prokaryote and the gut microbiome

In a conventional view of the prokaryotic genome organization, promoters precede operons and ribosome binding sites (RBSs) with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS-2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of precomputed "heuristic" models designed to identify harder-to-detect genes (likely horizontally transferred). Importantly, we designed GeneMarkS-2 to identify several types of distinct sequence patterns (signals) involved in gene expression control, among them the patterns characteristic for leaderless transcription as well as noncanonical RBS patterns. To assess the accuracy of GeneMarkS-2, we used genes validated by COG (Clusters of Orthologous Groups) annotation, proteomics experiments, and N-terminal protein sequencing. We observed that GeneMarkS-2 performed better on average in all accuracy measures when compared with the current state-of-the-art gene prediction tools. Furthermore, the screening of ∼5000 representative prokaryotic genomes made by GeneMarkS-2 predicted frequent leaderless transcription in both archaea and bacteria. We also observed that the RBS sites in some species with leadered transcription did not necessarily exhibit the Shine-Dalgarno consensus. The modeling of different types of sequence motifs regulating gene expression prompted a division of prokaryotic genomes into five categories with distinct sequence patterns around the gene starts.

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Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes.

Differential RNA-Seq (dRNA-Seq) is a recently developed method of performing primary transcriptome analyses that allows for the genome-wide mapping of transcriptional start sites (TSSs) and the identification of novel transcripts. Although the transcriptomes of diverse bacterial species have been characterized by dRNA-Seq, the transcriptome analysis of archaeal species is still rather limited. Therefore, we used dRNA-Seq to characterize the primary transcriptome of the model archaeon Haloferax volcanii. Three independent cultures of Hfx. volcanii grown under optimal conditions to the mid-exponential growth phase were used to determine the primary transcriptome and map the 5′-ends of the transcripts. In total, 4749 potential TSSs were detected. A position weight matrix (PWM) was derived for the promoter predictions, and the results showed that 64 % of the TSSs were preceded by stringent or relaxed basal promoters. Of the identified TSSs, 1851 belonged to protein-coding genes. Thus, fewer than half (46 %) of the 4040 protein-coding genes were expressed under optimal growth conditions. Seventy-two percent of all protein-coding transcripts were leaderless, which emphasized that this pathway is the major pathway for translation initiation in haloarchaea. A total of 2898 of the TSSs belonged to potential non-coding RNAs, which accounted for an unexpectedly high fraction (61 %) of all transcripts. Most of the non-coding TSSs had not been previously described (2792) and represented novel sequences (59 % of all TSSs). A large fraction of the potential novel non-coding transcripts were cis-antisense RNAs (1244 aTSSs). A strong negative correlation between the levels of antisense transcripts and cognate sense mRNAs was found, which suggested that the negative regulation of gene expression via antisense RNAs may play an important role in haloarchaea. The other types of novel non-coding transcripts corresponded to internal transcripts overlapping with mRNAs (1153 iTSSs) and intergenic small RNA (sRNA) candidates (395 TSSs). This study provides a comprehensive map of the primary transcriptome of Hfx. volcanii grown under optimal conditions. Fewer than half of all protein-coding genes have been transcribed under these conditions. Unexpectedly, more than half of the detected TSSs belonged to several classes of non-coding RNAs. Thus, RNA-based regulation appears to play a more important role in haloarchaea than previously anticipated.

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Genome-wide identification of transcriptional start sites in the haloarchaeon Haloferax volcanii based on differential RNA-Seq (dRNA-Seq)

RNA-seq technologies have provided significant insight into the transcription networks of mycobacteria. However, such studies provide no definitive information on the translational landscape. Here, we use a combination of high-throughput transcriptome and proteome-profiling approaches to more rigorously understand protein expression in two mycobacterial species. RNA-seq and ribosome profiling in Mycobacterium smegmatis, and transcription start site (TSS) mapping and N-terminal peptide mass spectrometry in Mycobacterium tuberculosis, provide complementary, empirical datasets to examine the congruence of transcription and translation in the Mycobacterium genus. We find that nearly one-quarter of mycobacterial transcripts are leaderless, lacking a 5’ untranslated region (UTR) and Shine-Dalgarno ribosome-binding site. Our data indicate that leaderless translation is a major feature of mycobacterial genomes and is comparably robust to leadered initiation. Using translational reporters to systematically probe the cis-sequence requirements of leaderless translation initiation in mycobacteria, we find that an ATG or GTG at the mRNA 5’ end is both necessary and sufficient. This criterion, together with our ribosome occupancy data, suggests that mycobacteria encode hundreds of small, unannotated proteins at the 5’ ends of transcripts. The conservation of small proteins in both mycobacterial species tested suggests that some play important roles in mycobacterial physiology. Our translational-reporter system further indicates that mycobacterial leadered translation initiation requires a Shine Dalgarno site in the 5’ UTR and that ATG, GTG, TTG, and ATT codons can robustly initiate translation. Our combined approaches provide the first comprehensive view of mycobacterial gene structures and their non-canonical mechanisms of protein expression.

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Mushtaq Mir

Papers

Leaderless Transcripts and Small Proteins Are Common Features of the Mycobacterial Translational Landscape.