From microbial gene essentiality to novel antimicrobial drug targets
© Mobegi et al.; licensee BioMed Central Ltd. 2014
Received: 22 April 2014
Accepted: 23 October 2014
Published: 5 November 2014
Bacterial respiratory tract infections, mainly caused by Streptococcus pneumoniae, Haemophilus influenzae and Moraxella catarrhalis are among the leading causes of global mortality and morbidity. Increased resistance of these pathogens to existing antibiotics necessitates the search for novel targets to develop potent antimicrobials.
Here, we report a proof of concept study for the reliable identification of potential drug targets in these human respiratory pathogens by combining high-density transposon mutagenesis, high-throughput sequencing, and integrative genomics. Approximately 20% of all genes in these three species were essential for growth and viability, including 128 essential and conserved genes, part of 47 metabolic pathways. By comparing these essential genes to the human genome, and a database of genes from commensal human gut microbiota, we identified and excluded potential drug targets in respiratory tract pathogens that will have off-target effects in the host, or disrupt the natural host microbiota. We propose 249 potential drug targets, 67 of which are targets for 75 FDA-approved antimicrobials and 35 other researched small molecule inhibitors. Two out of four selected novel targets were experimentally validated, proofing the concept.
Here we have pioneered an attempt in systematically combining the power of high-density transposon mutagenesis, high-throughput sequencing, and integrative genomics to discover potential drug targets at genome-scale. By circumventing the time-consuming and expensive laboratory screens traditionally used to select potential drug targets, our approach provides an attractive alternative that could accelerate the much needed discovery of novel antimicrobials.
The World Health Organization (WHO; http://www.who.int) ranks respiratory tract infections (RTI) among the ten leading causes of global mortality. RTI are associated with several bacterial species, of which Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis are the most prevalent community-acquired respiratory bacterial pathogens . In healthy individuals, these species colonize mucosal surfaces of the upper airways in a commensal state. Their relevance as pathogens arises when they infiltrate and colonize the otherwise sterile spaces in the middle ear, lung or bloodstream, progressing to disease . With the mounting inexorable resistance of these pathogens against several commonly used antimicrobials , discovery of new protein targets against which new antibiotics could be developed will highly benefit global healthcare management of RTI.
Elucidation of genes essential for bacterial growth and viability is a prerequisite for identifying potential drug targets . Essential genes are highly conserved and are thus considered as favourable drug targets for broad-spectrum inhibition . On the other hand, some metabolic pathways constitute crucial transport and catalytic proteins which could also form attractive drug targets. Furthermore, most pathogens have drastically reduced their biosynthetic capabilities, and instead rely on their hosts to provide vital nutrients like amino acids, vitamins, and nucleobases . Transport systems for these nutrients are generally conserved and indispensable for survival of the pathogen in its host , making them promising drug targets. In order to qualify as drug targets, microbial genes should meet several requirements. First, they should be nonhomologous to human genes to avoid drug cytotoxicity . Additionally, targets should either be completely absent, or catalytically distinctive from genes found in host gut commensal microbiota, whose perturbation is likely to be detrimental to human nutrition, health, and physiology . It has been shown that antibiotic killing of commensal microbiota facilitates proliferation, and often dominance, of antibiotic-resistant pathogens on mucosal surfaces . Lastly, candidate drug targets must be accessible by inhibitors. Essential surface/membrane and secreted proteins are particularly promising, having been successfully targeted by protein drugs, and representing majority of all known drug targets [9, 10].
Previous microbial gene essentiality predictions employed techniques generally limited in specificity and/or throughput [11, 12]. These shortcomings are alleviated by high-throughput transposon insertion sequencing strategies, such as Tn-seq, TraDIS, INseq, or variants thereof, which have been applied in recent studies to comprehensively essay gene essentiality and genetic interactions in various bacteria [13, 14]. Here, we applied Tn-seq to reliably identify essential genes in S. pneumoniae, H. influenzae and M. catarrhalis. Products of these genes were compared against the human proteome, and the catalogue of genes from human gut commensal microbes, to identify and eliminate targets likely to have off-target effects in the host or on the host’s gut microbiota. Two out of four of the finally identified novel drug targets have been successfully validated using existing inhibitors. This study pioneers an integrative approach for rapid and cost-effective identification of novel drug targets. Our findings do not only improve the overall understanding of respiratory pathogens, but also serve as a proof of concept for the robust yet underexploited approaches, combining in silico and wet laboratory analyses in identifying antimicrobial drug targets, as recently reviewed . This approach has allowed us to identify promising drug target leads, which after experimental validation could be potentially advanced to the discovery of novel antimicrobials for the treatment of RTI.
Bacterial genomes and gene reannotation
Whole genome sequences for S. pneumoniae TIGR4 uid57857, S. pneumoniae R6 uid57859, H. influenzae Rd KW20 uid57771, H. influenzae 86 028NP uid58093 and M. catarrhalis BBH18 uid48809 were obtained from the National Centre for Biotechnology Information (NCBI) Genbank File Transfer Protocol (FTP) website (ftp://ftp.ncbi.nih.gov/genbank/). All open reading frame (ORF) annotations were updated using Rapid Annotation using Subsystem Technology (RAST) . In this analysis, all locus coordinates in original Genbank genomes release were retained without adjustments for frame-shifts.
Orthology and gene essentiality predictions
We clustered the reannotated protein sequences into putative orthologous groups using the OrthoMCL standalone software Version 2.0.2 . Most studies have consistently deciphered essential genes under ideal conditions, that is, in the richness of all necessary nutrients and without environmental stress. For the purpose of this study, we define the “essentiality” of a gene as its indispensability under rich media conditions, unless stated otherwise. The caveat with this approach is that essential genes required for metabolism within the host may be missed.
Transposon mutant libraries used were either created in-house for this study, or obtained from literature and reanalysed. The M. catarrhalis BBH18 marinerT7 transposon mutant libraries consisting of 28,000 and 7,000 independent transformants were previously described [18, 19], and the 12,500 transformants library was generated using the previously described protocol . The 40,000 transformants S. pneumoniae R6 and the 11,000 transformants H. influenzae 86 028NP library were previously described [20, 21]. Libraries for the 15,000 transformants S. pneumoniae R6 and H. influenzae Rd KW20 were also respectively constructed as previously described [20, 21]. The Tn-seq technology was used to profile the relative abundance of each mutant in all libraries after growth as described previously , except for S. pneumoniae TIGR4. Tn-seq data for S. pneumoniae TIGR4 were obtained from literature . We then performed essentiality predictions for individual genes using the in-house developed web-tool, ESSENTIALS , which enabled us calculate a statistical essentiality metric for each ORF, and precisely delineate the optimal boundary between essential and nonessential ORFs in each of the 5 strains. Analysis data can be found at http://bamics2.cmbi.ru.nl/websoftware/essentials/links.html.
Overrepresented metabolic pathways and subsystems
Pathways and subsystems for the strains under study were obtained from the Kyoto Encyclopedia of Genes and Genomes orthology, and the SEED databases respectively [25, 26]. Using a Fisher’s exact test, we performed functional categories enrichment for the pathways and subsystems, while incorporating the statistical essentiality value (the fold-change value predicted by ESSENTIALS) for each ORF. We corrected for multiple testing using Bonferroni correction and obtained q-values for corresponding p-values .
Proteins subcellular localization (SCL)
The subcellular localizations (SCL) of all proteins in this study were determined using publicly available SCL prediction tools. First, we analysed all Gram-positive and Gram-negative strains using pSORTdb version 2.0  and CELLO version 2.5 . Further complementation SCL predictions were performed using LocateP and GnegPloc for Gram-positive and Gram-negative strains respectively [29, 30]. Additionally, the presence of integral Gram-negative outer membrane proteins (OMP) was determined using β-barrel outer membrane protein predictor (BOMP) . Proteins that showed different SCL predictions in the different predictors used were denoted “Unknown”, together with those predicted to be of unknown SCL by majority of the predictors used.
Selecting potential drug targets
To identify and eliminate essential genes with close undesirable orthologs, we performed separate unidirectional protein-protein BLAST (BlastP) searches, using an E-value cut-off of 1e-10, and minimum 70% sequence identity over 75% sequence coverage; against the human genome, and the metagenomics catalogue of non-redundant human gut microbiome genes by Qin et al..
Determination of antimicrobial activity
Selection of potential drug targets for in vivo validation was mainly based on their novelty, that is, they have not been described as targets to existing antimicrobials. Commercial availability of inhibitory compounds without resorting to customized chemical synthesis was also key; all inhibitory compounds used were supplied by Sigma Aldrich. 1-Methyluric acid, 5, 5′-Dithio-bis-(2-nitrobenzoic Acid), and 5′-deoxyadenosine were dissolved in water at 5 mg/ml. When necessary, the pH was neutralized (to pH7) using 10 M NaOH solution or 1 M HCl. Antimicrobial activity of the compounds was tested by Kirby-Bauer/disk diffusion assay , by applying 10 μg of the inhibitory compounds to 6 mm filter paper discs at concentration ranging from 10000 to 0.05 μg/ml in 10-fold stepwise dilutions. As for (R)-6-fluoromevalonate diphosphate 2 μl of (R)-6-fluoromevalonate diphosphate was diluted in 1 ml of Milli-Q (MQ). 10 μl and 100 μl of the dilution was used in separate disk diffusion assays. Columbia III agar with 5% sheep blood medium was used for S. pneumoniae. Brain heart infusion (BHI) agar medium, and a combination medium of BHI, hemin, and NAD were used for M. catarrhalis and H. influenzae respectively. MIC calculations were performed as described by Wiegand and colleagues . Experiments were performed in quadruplicate, and outliers were removed using the Grubbs test .
Toxicity assays on epithelial cell lines
Cellular toxicity of (R)-6-fluoromevalonate diphosphate was tested using the CellTox Green Cytotoxicity Assay (Promega, WI) on Detroit 562 (ATCC CCL-138) and A549 (ATCC CCL-185) cell lines according to the manufacturer’s instructions. The two cell lines were exposed to (R)-6-fluoromevalonate diphosphate at its effective MIC concentration of 26.6 μg/ml for 24 hours at 37°C with 5% CO2. Fluorescence was measured on a Perkin Elmer 1420 Victor 3 V multi-label plate reader.
Results and discussion
Genome reannotation and gene clustering
Strain genome annotation updates and essentiality predictions
Total number of ORFs
ORFs with hypothetical function in genome
ORFs with hypothetical function after RAST
Number of insertion sites a
Log2fold change cut-off b
Mutant library size (CFU)
Number of sequenced reads c
Total essential genes
S. pneumoniae R6
S. pneumoniae TIGR4
6 × 20,000
H. Influenzae 86 028NP
H. influenzae Rd KW20
M. catarrhalis BBH18
Essential and conserved protein-coding genes
Loss of mutant readouts from a transposon library after in vitro transposition and genetic transformation of the wild-type isolate is a strong indicator of gene essentiality . Although some essential genes tolerate disruptive insertions in the 3′ regions, generally, insertions in essential genes lead to lethal phenotypes . For our analysis, mutant libraries and/or Tn-seq data were constructed in in-house experiments or obtained from literature (Table 1). We separately analysed the Tn-seq datasets using ESSENTIALS . This analysis resulted in the identification of 532 essential genes in H. influenzae 86-028NP, representing 28% of the genome, a higher number as compared to the other Gram-negative strains; H. influenzae Rd KW20 and M. catarrhalis BBH18, in which we identified 431 and 445 essential genes respectively. In S. pneumonia, we identified 325 and 414 essential genes for the R6 and TIGR4 strains respectively (Table 1; Additional file 1). These values showed that on average, about 20% of all genes in the five strains are essential. This is consistent with earlier studies which have reported 15-25% of all genes in a genome being essential [23, 36, 37].
Differences in the number of essential genes could be explained by various factors that hamper precision in transposon mutagenesis experiments, including short gene lengths and unsaturated transposon libraries; “saturation” being the presence of at least one insertion in every gene. In practice, short genes are less susceptible to disruptive transposon insertions, hence, more likely to be misclassified as essential. In unsaturated transposon mutant libraries, dispensable genes are also more likely to be devoid of transposon insertions, and therefore misclassified as being essential genes. The low-density transposon mutant library (approximately 11,000 colony forming units; CFU) used for H. influenzae 86-028NP, and a substantial number of short genes in its genome could, therefore, explain the apparently overestimated (532) essential genes. Relatively saturated libraries of approximately 20,000 CFU and 40,000 CFU were used for H. influenzae Rd KW20 and M. catarrhalis BBH18 respectively (Table 1). A rarefaction analysis on our data confirmed that the S. pneumoniae, M. catarrhalis, and H. influenzae Rd KW20 transposon libraries approached saturation (Additional file 2). Additionally, based on derivations of Poisson’s law, there is a 99.6% probability that genes with a size of 1 kb are hit in the 1.9 Mb H. influenzae 86-028NP genome and an 11,000 CFU mutant library. Similar statistics on the 1.79 Mb H. influenzae Rd KW20 genome with a 20,000 CFU mutant library shows a 99.99% probability. Therefore, H. influenzae 86-028NP could have suffered slightly more false positive predictions due to its less saturated mutant libraries.
Essential metabolic pathways and subsystems
Distribution of essential features among respiratory pathogens
Quantity in the strain
Essential structural and non-coding RNAs
Essential Protein-coding ORFs
Protein of unknown functions
Genetic Information Processing
Environmental Information Processing
Overrepresented/essential KEGG pathways
Genetic Information Processing
Environmental Information Processing
Overrepresented/essential SEED subsystems
Cofactors, Vitamins, Prosthetic Groups, Pigments
Cell Wall and Capsule
Amino Acids and Derivatives
Fatty Acids, Lipids, and Isoprenoids
Nucleosides and Nucleotides biosynthesis
Virulence, Disease and Defence
Regulation and Cell Signalling
Cell Division and Cell Cycle
Protein subcellular localization
Out of the 705 OGs selected, the majority (526) consists of cytoplasmic proteins. Cellular localization of the other OGs were predicted to be: 96 in the inner membrane, 11 in the outer membrane, 12 in the periplasm, and 4 in the extracellular space. In addition, 21 OGs are non-categorically predicted to contain membrane proteins, whereas 35 are of unknown localizations. Of the 11 outer membrane OGs, 7 contained β-barrels (Additional file 1).
Orthologs in human and human gut microflora
The human gut is home to microbiota whose proper composition and functioning collectively influence human nutrition, protection against pathogens and development of disease . Perturbing this microbiota with antibiotics could cause adverse side effects. Furthermore, interference with human cell physiology by antibiotics as a consequence of non-specific targeting can cause severe cellular cytotoxicity , which may result in organ failure or even death. We used blastP analyses against the human genome (Genome Reference Consortium) and the human gut microbial gene catalogue , to identify targets that would likely have off-target effects. It is noteworthy that targets with as few as 10 matches in the non-redundant gut microbial gene catalogue were allowed in the final selection, as we hypothesised that these would have no effects on the gut microbiome preventing disruption of gut health. This decision was motivated by the observation from our analysis that well known targets for both clinically approved antimicrobials and experimental small molecule inhibitors collated in DrugBank (Additional file 1; column 9) maintained on average fewer than 10 blast hits against the human gut microbial gene catalogue (Additional file 1; column 20). On the other hand, the majority of the targets with numerous blast hits were aminoacyl-tRNA synthetases (aaRSs) and ribosomal protein, including rpsL, a well-known target that had 249 hits for pneumococci, 156 for H. influenzae, and 151 for M. catarrhalis. One shortcoming of using such filtering criteria is that novel targets that have more than 10 blast hits are not effectively retained in the final selection. Nevertheless, we identified 96 OGs with orthologs in human, and 127 OGs with orthologs in human gut microflora, that is, with >10 blast hits (Additional file 1). All 20 aminoacyl-tRNA synthetases (aaRSs), essential for protein synthesis, were particularly conserved in both human and human gut microflora. Studies have shown that aaRSs can be selectively targeted as most bacterial aaRSs recognize and aminoacylate only cognate tRNA . However, possible side effects are expected from drugs targeting aaRSs. RNA molecules and ribosomal proteins were also highly conserved in gut microbiota and humans. Additionally, the relatively short lengths and the presence of highly repetitive DNA in RNA sequences also rendered their essentiality predictions unreliable. All these molecules were therefore not included in the final selection of drug targets. Moreover, blast comparison between finally selected targets and their human orthologs showed minimal sequence identities (<35%) over short sequence coverage.
Drug targets selection and validation
We identified 249 potential drug targets in the five strains (Additional file 5), including key enzymes in pathways such as fatty acid biosynthesis [39–41], vitamin biosynthesis [42–45], and isoprenoid biosynthesis pathways [46–48], which have gained interest in drug discovery research, as well as 67 known targets inhibited by 75 FDA-approved antimicrobial drugs and 35 other researched small molecule inhibitors collated in the DrugBank database . To validate our target prediction, we selected four novel targets with commercially available novel inhibitors of their predicted essential functions, that is, inhibitors not yet approved as clinical drugs and don’t require to be custom synthesized: We tested whether exposure to these compounds inhibited growth of the target organisms.
Drug target in vivo validation summary
Amount on disc (μg)
MIC μg/ml; Std. Dev. [Inhibition area on disk diffusion assay]
5,5′-dithiobis(2-nitrobenzoate) (CAS 69-78-3)
2,500; 0 [4 mm*]
781; 313 [none]
319; 303 [none]
1-methyluric acid (CAS 708-79-2)
>312.5 [6 mm]
5′deoxyadenosine (CAS 4754-39-6)
78.1; 0 [6 mm]
205; 132 [5 mm*]
29.3; 11 [12 mm]
(R)-6-fluoromevalonate diphosphate (CAS 2822-77-7)
26.6; 11.5 [12 mm]
4,167; 1443 [none]
>5,000; 0 [none]
(R)-6-fluoromevalonate diphosphate (CAS 2822-77-7)
26.6; 11.5 [4 mm*]
4,167; 1443 [none]
>5,000; 0 [none]
The microbial fatty acid synthesis (FAS) pathway is an attractive target for drug discovery [41, 57]. This pathway is subdivided into type I and II, whereby human FAS proteins predominantly belong to type I FAS, and the bacterial ones are predominantly type II FAS. Proteins from the two FAS types generally possess distinctive molecular organization of the active site allowing for selective targeting [39, 40]. Although Gram-positive pathogens could compensate FASII inhibition by assimilating environmental fatty acids; particularly unsaturated fatty acids [58, 59], several clinical and household antimicrobials targeting key FAS enzymes, e.g. Platensimycin and Platencin have been successfully developed [41, 60]. In our analysis, we identified various genes conserved in all five strains, for example genes in OGs 085, 143, and 653, whose products play key roles in the FAS pathway. With 5′-Deoxyadenosine (CAS: 4754-39-6), we targeted lipoate synthase (LipA; EC: 18.104.22.168), a key enzyme in the lipoic acid metabolism , using product-level inhibition. Surprisingly, we observed growth inhibition in all three species (Figure 3; Table 3), despite the target cluster (OG_653) comprising of orthologs from only Gram-negative strains (Additional file 1). This observations are also reflected in the MIC, which ranged from 29.3 to 205.1 μg/ml (Table 3). A blastP comparison showed that the closest ortholog of the Gram-negative LipA in S. pneumoniae is the non-lipoic pathway enzyme fructose-6-phosphate aldolase I, sharing about 32% sequence identity. Moreover, a comparison between LipA and lipoate-protein ligase (LplA), the key lipoylation enzyme in S. pneumoniae, revealed that the two proteins are non-orthologous, as they share very low sequence identity (<25%). They however have conserved domain which may explain the observed growth inhibition.
Isoprenoids are natural products involved in many biochemical functions, such as supplying quinones for the electron transport chains, components of membranes, and subcellular targeting and regulation . Humans employ the mevalonate pathway, whereas most microbes follow a non-mevalonate (1-deoxy-d-xylulose 5-phosphate/2-C-methyl-d-erythritol 4-phosphate) pathway. Functional roles of key enzymes in the isoprenoid biosynthesis pathway are well characterized, opening prospects for the discovery of novel drug targets [46, 48]. Fosmidomycin is a promising isoprenoid-based anti-malarial drug which is currently in clinical trials . Using 6-fluoromevalonate (CAS: 2822-77-7) to target diphosphomevalonate decarboxylase (EC: 22.214.171.124), we observed selective growth inhibition only in S. pneumoniae as expected (Figure 3; Additional file 1; Table 3). Additionally, no effects on growth were observed in the Gram-negative strains, which was also as expected. We determined an average MIC of value 26.6 μg/ml for the S. pneumoniae growth inhibition (Table 3). At 26.6 μg/ml, no toxicity was observed in cell toxicity assays on epithelial cell lines (data not shown). Moreover, in patent WO 1995013058 A1, no cytotoxic effects of 6-fluoromevalonate were observed on T-lymphocytes. Previous literature also shown that 6-fluoromevalonate could potentially function the same as statins, as they inhibit the same pathway . Diphosphomevalonate decarboxylase could therefore be a promising target for developing novel antibiotics against S. pneumoniae.
We have combined Tn-seq with in silico approaches to obtain an insight into many essential and conserved molecular functions, which we predicted to be unique among respiratory pathogens. With this combinatorial approach, we have reliably identified 249 potential drug targets, 67 of which are acknowledged targets for 75 FDA-approved antimicrobial drugs and 35 other researched small molecule inhibitors ; we successfully validated two of the four tested targets. Here, we propose a number of novel potential drug targets that are a concrete lead for experimental validation. We anticipate that future research based on this study will eventually provide interesting targets that can be successfully moved to drug development. In conclusion, we have pioneered a powerful approach, which combines microbial gene essentiality data with robust computational techniques, to comprehensively screen for antimicrobial drug targets at genome-scale. This approach circumvents the complex and costly laboratory screens, thus, facilitating directed drugs discovery.
Availability of supporting data
The data sets supporting the results of this article are included within the article and its additional files. Tn-Seq data sets are available in the European Nucleotide Archive repository, [http://www.ebi.ac.uk/ena/data/view/PRJEB7553].
This work was supported by funding from the European Commission FP7 Marie Curie IEF Action [274586 to AZ] and the Netherlands Genomics Initiative Horizon Breakthrough [93518023 to PB].
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