University of Groningen
Quantifying the transcriptome of a human pathogen
Aprianto, Rieza
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2018
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Aprianto, R. (2018). Quantifying the transcriptome of a human pathogen: Exploring transcriptional
adaptation of Streptococcus pneumoniae under infection-relevant conditions. Rijksuniversiteit Groningen.
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6
Discussion
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RN
A: mor
e than a middle man
RNA: more than a middle man
The central dogma states that a gene, made of DNA, transcribes informa-tion to a transcript made of RNA, which in turn is translated into a protein, the main cellular work-horse1. The dogma insinuates that the transcript
is a simple baton between the repository of information and the effector. Actually, RNA can directly regenerate a copy of itself, also known as RNA replication. Moreover, RNA can transcribe DNA, reverting the dogmatic information flow. On the other hand, novel developments in sequencing technology and recent studies have revealed an expanded RNA function in the regulation of gene expression, including modifying the abundance of transcripts and efficiency of translation. Finally, the genome-wide quantification of transcripts has been made easy by the advent of next generation sequencing.
The opportunistic human pathogen, Streptococcus pneumoniae, em-ploys manifold strategies to orchestrate its gene expression. An import-ant class, the stand-alone regulator, is mediated by a protein binding directly to DNA to regulate downstream expression. For example, CcpA, the carbon catabolite protein, has a sensing domain and a DNA-binding domain, moonlighting two roles in one molecules2. Another type of a
pro-tein-based regulator, the two component systems (TCSs), separate these functions by a membrane-bound sensor and a cytoplasmic DNA-binding regulator. Specifically, TCSs architecture makes it suitable to detect envi-ronmental signals3.
On the other hand, pneumococcal RNA-based regulation has not been fully appreciated with only intermittent studies available4. This is wholly
surprising, since RNA-mediated gene regulation is highly suitable for
S. pneumoniae facing a dynamic environment during colonization,
trans-mission and infection. First, RNA as gene regulator is more economical to the cell than expressing a protein to control expression, simply because transcribing RNA does not require an investment into amino acids5. For
example, high-cost enzymes are mostly controlled at the transcriptional level in other bacteria6, emphasizing resource-prudent decision-making
in order to conserve cellular resources, such as amino acids and tRNAs. Secondly, RNA molecules are generally less stable than a protein7, highly
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suitable for mediating transient regulation. Recent transcriptomics stud-ies further support this hypothesis by highlighting the ubiquity of pneu-mococcal non-coding small RNAs and thus, the potential of RNA-based
regulations8–10. Pneumococcal gene regulation may also benefit by
com-bining RNA- and protein-based regulators, for example, five sRNAs under the control of CiaRH have been reported to have wide-ranging effects on
pneumococcal phenotypes11,12. Lastly, pneumococcal riboswitches have
not been formally described, aside from orthology-based reports4.
These central roles of transcripts in the cellular function of S.
pneumo-niae including in the development of pathogenesis served as the context
of our study into the pneumococcal genomic repertoire. In Chapter 2, we
employed cutting-edge sequencing technology to thoroughly define the pneumococcal genome-transcriptome and to revise the genome-wide annotation, including non-coding RNAs. Furthermore, we reported abundant transcription from the antisense strand (asRNAs), overlapping coding sequences and untranslated regions. The abundance of antisense RNAs can directly regulate gene expression in a cis-acting manner. In ad-dition, we observed significant transcriptional starting sites (TSS, +1) in the middle of the annotated coding sequence or putative operon. The presence of internal transcriptional start sites (iTSSs) may suggest an al-ternative regulation of genes within operons. Even more, antisense and internal transcription might be activated in response to certain environ-mental signals as an adaptive measure to expand phenotypic plasticity.
Furthermore, in Chapter 2, we have re-categorized four small genomic
features as uridine-responsive riboswitches. During uridine abundance, the riboswitch destabilizes an antiterminator hairpin, causing early termi-nation and switching off the downstream expression13. Moreover, a recent
study showed an early termination to be independent of PyrR, a repres-sor previously thought to be essential in facilitating riboswitch function14.
Riboswitch-based gene regulation has been proposed to be more bene-ficial in Gram positive than Gram negative bacteria, due to the generally more compact genome and longer operons in Gram positive bacteria5. For
instance, Bacillus subtilis, a Gram positive model organism, puts 2% of its genes under the control of riboswitches5. In addition, regulation by
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of gene expression, at both the transcriptional and translational levels15.
Lastly, RNA fragments originating from early termination events may act as trans-acting sRNA16, further moonlighting its regulatory function. In
all, our genome and curated annotation will provide the chassis for future work on pneumococcal genomics. At the same time, our work contrib-uted to the perspective of RNA-mediated gene regulation in S.
pneumo-niae. Chapter 2 re-emphasizes the role of RNA-based gene regulation in S. pneumoniae by highlighting the genomic potential of RNA features
in-cluding riboswitches, UTRs and sRNAs in fine tuning selected transcrip-tion and translatranscrip-tion.
Quantifying infection: genome-wide transcript abundance
in models
The glaring lack of pathogenicity islands suggests that pneumococcal virulence and further pathogenesis are more subtly regulated17–19, for
ex-ample via mutation in untranslated regions (UTRs). In addition, recent advances in sequencing technology have allowed precise quantification of transcript abundance20. In Chapter 3, we combined the quantification
of total RNA with an array of in vitro infection-relevant models, persuad-ing the bacteria to express a compendium of expression in response to a wide range of microenvironments. The approach has been applied to other relevant bacteria21–24, usually in conjunction with the elucidation of
start sites. In this study, we observed that transcriptional levels of genes involved in core cellular functions, such as carbon metabolism, transcrip-tion and translatranscrip-tion, are conserved across varying conditranscrip-tions.
In this study, we did not deplete bacterial rRNA thereby avoiding the bias introduced by depletion25. Here, we have observed that rRNAs occupy
around 95% of transcripts while tRNAs take up less than 1% of total tran-scripts. Subsequently, transcript abundance was transformed into a co- expression matrix, a form of gene network. We combined correlation val-ues of neighboring genes, start sites and terminator sites (from Chapter 2)
to map genome-wide putative operons. The co-expression matrix may serve as a base to build gene regulatory networks by inferring regula-tion among genomic features. By exploiting this method, we revealed
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gene had not been observed as part of the competence regulon in pre-vious array-based studies26,27, exemplifying the power of next- generation
sequencing in transcriptomics quantification.
In Chapter 4, we used RNA-sequencing to determine a suitable
re-porter gene to tag with a fluorescent protein. We selected HlpA, a highly transcribed protein and the only histone-like protein in Streptococcus28.
Furthermore, we followed the fluorescent pneumococcal reporter strain in several infection-relevant models, including during co-incubation with live confluent human lung epithelial cells. The exposure of S. pneumoniae to confluent epithelial layers has been shown to reflect a biotic surface as present in vivo, and it stimulates different phenotypic responses com-pared to growth in liquid broth or growth on a plastic abiotic surface29.
Moreover, we included an unencapsulated strain in the study. The unen-capsulated derivative showed better adherence to epithelial cells than the ancestral encapsulated strain. In addition, the pneumococcal polysaccha-ride capsule is an essential virulence factor that determines colonization and infection success; it also serves as a vaccine target30.
We then exploited the co-incubation model including the unencap-sulated strain to simultaneously sequenced the host and pathogen tran-scripts during the progression of early infection (Chapter 5). Since the
unencapsulated strain better adheres to epithelial cells, these bacteria have more intimate contact with the monolayer than its encapsulated, mostly planktonic, strain. By comparing transcriptional responses between unen-capsulated and wild type models, we elucidated adherence-specific tran-scriptional responses in both epithelial and pneumococcal transcriptomes. Because adherence is the first step towards pathogenesis, adherence- specific regulated genes might provide interesting novel drug and/or vac-cination targets that have not yet been identified by conventional screens aimed at targeting essential and/or surface exposed proteins. Nevertheless, future work to precisely identify useful targets is required.
In Chapter 5, we have developed a rapid RNA isolation technique to
ter-minate the protein-based RNA production and digestion allowing precise kinetics observations. Furthermore, in cooperation with EMBL Genomics Core Facility, we developed a one-step dual rRNA depletion to remove both human and bacterial-derived rRNAs. We further exploited the bright
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fluorescent strain (from Chapter 4) to visualize epithelial- adherent
bacte-ria during the progression of early infection. In addition, we showed that the activity of promoter-of-interest can be measured by fluorescence tag-ging and live microscopy. Also, we have shown that the adherent bacteria modulate the innate immune response of epithelial cells to their advan-tage while importing host-associated sugars as a carbohydrate source to fuel bacterial expansion.
Remarkably, we observed that all pneumococcal genes are expressed at one point or another during the infection process (Chapter 5).
We no-ticed the same observation in Chapter 3 when the bacteria were exposed
to conditions relevant to its lifestyle. While this might partly stem from the high sequencing depth undertaken in these studies, other genome- wide bacterial gene expression studies confirm the abundant bacterial tran-scription21,22. We speculate that dynamic conditions, including interspecies
interaction, necessitates massive pneumococcal transcriptional adapta-tion. Additionally, we have also shown that the whole of the genome can be transcribed due to ubiquitous transcriptional start sites (Chapter 2). To
summarize, Chapters 3 and 5 highlights the suitability of transcriptomics
(i.e. genome-wide quantification of transcriptional responses) in elucidat-ing the highly complicated interaction between the bacteria and its im-mediate microenvironment, both abiotic and biotic components, during the progression of colonization and infection. High throughput RNA-seq, combined with suitable harvesting methods offers a snapshot into the continuous interaction between S. pneumoniae and the components of microenvironment.
Furthermore, in all chapters, we have strived to disseminate the results of our research as widely as possible. First and foremost, we have been using open access platforms to publish our results. It should be noted that transcriptome databases only exist for few model bacteria such as Bacillus subtilis22,31, Staphylococcus aureus32, Escherichia coli33,34 and
Salmonella enterica Serovar Typhimurium35. Despite their paucity, these
resources have been proven to be invaluable resources for the research com-munity. Thereby, we have built easy-to-access online browsers for our data-sets (Chapters 2, 3 and 5) where users can simply choose a gene of interest
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The future: time to complicate matters
In the near future, further maturation of sequencing technologies prom-ises higher quality and more opportunities. Currently, indispensable sample preparations such as amplification and reverse transcription in-troduce bias to the data25; direct sequencing may remove these biases by
bypassing the sample preparations altogether36. Furthermore, current
technologies average individual responses into an aggregate population response. On the other hand, individual transcriptional changes in bacte-ria represents a meaningful diversity of responses, which, in turn, drives varying host responses37. Thus, a combination of direct sequencing and
single cell transcriptomics will open novel and powerful approaches in elucidating pneumococcal pathogenesis and other infectious agents. In addition, while genome-wide quantification of transcripts gives global impression of cellular protein abundance, the correlation between RNA and protein abundance is still limited (~0.7 to 0.8, in E. coli)38. Thus,
tran-scriptomics approaches benefit from complementary approaches, includ-ing proteomics and metabolomics.
Furthermore, the nasopharyngeal passage is a bustling ecosystem with numerous pneumococcal strains and onther bacteria39,40. Multiple strains
of S. pneumoniae can be present in the same individual host while occu-pying and competing for niche and resources. Furthermore, interstrain
competition has been enhanced by the pressure from vaccinations41 by
the replacement of target strains with non-vaccine serotypes. In addi-tion, while a study of the genomes of 44 clinical and model strains indi-cates that up to 74% of the genome is conserved42, strain-specific
tran-scriptional response to the colonization and infection sites may be more nuanced. The soon-available data on pneumococcal core genome and pan-genome from the Global Pneumococcal Sequencing project, where more than 20,000 pneumococcal genomes have already been sequenced (http://www.pneumogen.net/gps/) may serve as stepping stone to eluci-date the strain-specific responses.
Moreover, colonization and infection sites retain multispecies residents. S. pneumoniae competes for location and resources with
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influenzae, another common resident of the nasopharyngeal niche,
recruits host immune cells to hinder pneumococcal outgrowth44. Also,
dispersion biofilm models of either S. pneumoniae or S. aureus behave significantly different than a dual-species model, with co-colonization models causing early dispersion of S. pneumoniae and ending with
pneumococcal pneumonia45. Furthermore, in a murine co-infection
model of S. pneumoniae and influenza virus, pneumococci were found to utilize host- derived sugars to boost their own metabolism46. The
sug-ars were available as a result of the activity of viral enzymes. In these examples, the interaction is not necessarily direct but meaningfully changes the nature of pneumococcal virulence and pathogenesis in the host. In addition, the interaction within a polymicrobial environment has been reported to elicit a different set of essential genes in bacteria
altogether47. These reports highlight the complex system of
microbi-ota niches, including the respiratory tract, and interspecies interaction in infection. In order to explore host- pneumococcal interaction in the whole organism for real in vivo dual RNA-seq, we are investigating tran-scriptional responses in meningeal infection with zebrafish embryo of both host and pathogen responses. There, we are combining the pre-viously described infection model48 and a strain with inactivated
viru-lence factor, pneumolysin. Finally, we postulate that the combined ap-proach of multispecies infection model and avant-garde development of sequencing technology will uncover more clinically-relevant patho-genic interactions. The knowledge and insights ultimately may lead to novel vaccination strategies or new targets that can be used to prevent the expression of pneumococcal virulence factor and stop its pathogen-esis inside the human host.
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