Identification of Missing Carbon Fixation Enzymes as Potential Drug Targets in Mycobacterium Tuberculosis

In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlying Mycobacterium bovis infection

Objective

Bovine tuberculosis (bTB) is a chronic respiratory infectious disease of domestic livestock caused by intracellular Mycobacterium bovis infection, which causes ~$3 billion in annual losses to global agriculture. Providing novel tools for bTB managements requires a comprehensive understanding of the molecular regulatory mechanisms underlying the M. bovis infection. Nevertheless, a combination of different bioinformatics and systems biology methods was used in this study in order to clearly understand the molecular regulatory mechanisms of bTB, especially the immunomodulatory mechanisms of M. bovis infection.

Methods

RNA-seq data were retrieved and processed from 78 (39 non-infected control vs. 39 M. bovis-infected samples) bovine alveolar macrophages (bAMs). Next, weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression modules in non-infected control bAMs as reference set. The WGCNA module preservation approach was then used to identify non-preserved modules between non-infected controls and M. bovis-infected samples (test set). Additionally, functional enrichment analysis was used to investigate the biological behavior of the non-preserved modules and to identify bTB-specific non-preserved modules. Co-expressed hub genes were identified based on module membership (MM) criteria of WGCNA in the non-preserved modules and then integrated with protein-protein interaction (PPI) networks to identify co-expressed hub genes/transcription factors (TFs) with the highest maximal clique centrality (MCC) score (hub-central genes).

Results

As result, WGCNA analysis led to the identification of 21 modules in the non-infected control bAMs (reference set), among which the topological properties of 14 modules were altered in the M. bovis-infected bAMs (test set). Interestingly, 7 of the 14 non-preserved modules were directly related to the molecular mechanisms underlying the host immune response, immunosuppressive mechanisms of M. bovis, and bTB development. Moreover, among the co-expressed hub genes and TFs of the bTB-specific non-preserved modules, 260 genes/TFs had double centrality in both co-expression and PPI networks and played a crucial role in bAMs-M. bovis interactions. Some of these hub-central genes/TFs, including PSMC4, SRC, BCL2L1, VPS11, MDM2, IRF1, CDKN1A, NLRP3, TLR2, MMP9, ZAP70, LCK, TNF, CCL4, MMP1, CTLA4, ITK, IL6, IL1A, IL1B, CCL20, CD3E, NFKB1, EDN1, STAT1, TIMP1, PTGS2, TNFAIP3, BIRC3, MAPK8, VEGFA, VPS18, ICAM1, TBK1, CTSS, IL10, ACAA1, VPS33B, and HIF1A, had potential targets for inducing immunomodulatory mechanisms by M. bovis to evade the host defense response.

Conclusion

The present study provides an in-depth insight into the molecular regulatory mechanisms behind M. bovis infection through biological investigation of the candidate non-preserved modules directly related to bTB development. Furthermore, several hub-central genes/TFs were identified that were significant in determining the fate of M. bovis infection and could be promising targets for developing novel anti-bTB therapies and diagnosis strategies.

Deciphering the Proteomic Landscape of Mycobacterium tuberculosis in Response to Acid and Oxidative Stresses

The fundamental to the pathogenicity of Mycobacterium tuberculosis (Mtb) is the modulation in the control mechanisms that play a role in sensing and counteracting the microbicidal milieu encompassing various cellular stresses inside the human host. To understand such changes, we measured the cellular proteome of Mtb subjected to different stresses using a quantitative proteomics approach. We identified defined sets of Mtb proteins that are modulated in response to acid and a sublethal dose of diamide and H₂O₂ treatments. Notably, proteins involved in metabolic, catalytic, and binding functions are primarily affected under these stresses. Moreover, our analysis led to the observations that during acidic stress Mtb enters into energy-saving mode simultaneously modulating the acid tolerance system, whereas under diamide and H₂O₂ stresses, there were prominent changes in the biosynthesis and homeostasis pathways, primarily modifying the resistance mechanism in diamide-treated bacteria while causing metabolic arrest in H₂O₂-treated bacilli. Overall, we delineated the adaptive mechanisms that Mtb may utilize under physiological stresses and possible overlap between the responses to these stress conditions. In addition to offering important protein signatures that can be exploited for future mechanistic studies, our study highlights the importance of proteomics in understanding complex adjustments made by the human pathogen during infection.

The Effects of Carbon Source and Growth Temperature on the Fatty Acid Profiles of Thermobifida fusca

The aerobic, thermophilic Actinobacterium, Thermobifida fusca has been proposed as an organism to be used for the efficient conversion of plant biomass to fatty acid-derived precursors of biofuels or biorenewable chemicals. Despite the potential of T. fusca to catabolize plant biomass, there is remarkably little data available concerning the natural ability of this organism to produce fatty acids. Therefore, we determined the fatty acids that T. fusca produces when it is grown on different carbon sources (i.e., glucose, cellobiose, cellulose and avicel) and at two different growth temperatures, namely at the optimal growth temperature of 50°C and at a suboptimal temperature of 37°C. These analyses establish that T. fusca produces a combination of linear and branched chain fatty acids (BCFAs), including iso-, anteiso-, and 10-methyl BCFAs that range between 14- and 18-carbons in length. Although different carbon sources and growth temperatures both quantitatively and qualitatively affect the fatty acid profiles produced by T. fusca, growth temperature is the greater modifier of these traits. Additionally, genome scanning enabled the identification of many of the fatty acid biosynthetic genes encoded by T. fusca.

Protein Integrated Network Analysis to Reveal Potential Drug Targets Against Extended Drug-Resistant Mycobacterium tuberculosis XDR1219

The reconstruction and analysis of the protein-protein interaction (PPI) network is a powerful approach to understand the complex biological and molecular functions in normal and disease states of the cell. The interactome of most organisms is largely unidentified except some model organisms. The current study focused on the construction of PPI network for the human pathogen Mycobacterium tuberculosis (MTB)-resistant strain XDR1219 using computational methods. In this work, a bioinformatics approach was employed to reveal potential drug targets. The pipeline adopted the combination of an extensive integrated network analysis that led to identify 22 key proteins involved in drug resistance, resistant metabolic pathways, virulence, pathogenesis and persistency of the infection. The MTB XDR1219 interactome consists of 11,383 non-redundant PPIs among 1499 proteins covering 38% of the entire MTB XDR1219 proteome. The overall quality of the network was assessed and topological parameters of the PPI were calculated. The predicted interactions were functionally annotated and their relevance was assessed with the functional similarity. The study attempts to present the interactome of previously unidentified MTB XDR1219 and revealed potential drug targets that can be further explored by scientific community.

Higher genome variability within metabolism genes associates with recurrent Clostridium difficile infection

BACKGROUND

Clostridium difficile (C. difficile) is a major source of healthcare-associated infection with a high risk of recurrence, attributable to many factors such as usage of antibiotics, older age and immunocompromised status of the patients. C. difficile has also a highly diverse genome, which may contribute to its high virulence. Herein we examined whether the genome conservation, measured as non-synonymous to synonymous mutations ratio (dN/dS) in core genes, presence of single genes, plasmids and prophages increased the risk of reinfection in a subset of 134 C. difficile isolates from our previous study in a singly hemato-oncology ward.

METHODS

C. difficile isolates were subjected to whole-genome sequencing (WGS) on Ion Torrent PGM sequencer. Genomes were assembled with MIRA5 and annotated with prokka and VRprofile. Logistic regression was used to asses the relationship between single gene presence and the odds of infection recurrence. DN/dS ratios were computed with codeml. Functional annotation was conducted with eggNOG-Mapper.

RESULTS

We have found that the presence of certain genes, associated with carbon metabolism and oxidative phosphorylation, increased the odds of infection recurrence. More core genes were under positive selective pressure in recurrent disease isolates - they were mostly associated with the metabolism of aminoacids. Finally, prophage elements were more prevalent in single infection isolates and plasmids did not influence the odds of recurrence.

CONCLUSIONS

Our findings suggest higher genetic plasticity in isolates causing recurrent infection, associated mainly with metabolism. On the other hand, the presence of prophages seems to reduce the isolates' virulence.

Genomic profiling of antimicrobial resistance genes in clinical isolates of Salmonella Typhi from patients infected with Typhoid fever in India

The development of multidrug resistance in Salmonella enterica serovar Typhi currently forms a major roadblock for the treatment of enteric fever. This poses a major health problem in endemic regions and extends to travellers returning from developing countries. The appearance of fluoroquinolone non-susceptible strains has resulted in use of ceftriaxone as drug of choice with azithromycin being recommended for uncomplicated cases of typhoid fever. A recent sporadic instance of decreased susceptibility to the latest drug regime has necessitated a detailed analysis of antimicrobial resistance genes and possible relationships with their phenotypes to facilitate selection of future treatment regimes. Whole genome sequencing (WGS) was conducted for 133 clinical isolates from typhoid patients. Sequence output files were processed for pan-genome analysis and prediction of antimicrobial resistance genes. The WGS analyses disclosed the existence of fluoroquinolone resistance conferring mutations in gyrA, gyrB, parC and parE genes of all strains. Acquired resistance determining mechanisms observed included catA1 genes for chloramphenicol resistance, dfrA7, dfrA15, sul1 and sul2 for trimethoprim-sulfamethoxazole and bla_TEM-116/bla_TEM-1B genes for amoxicillin. No resistance determinants were found for ceftriaxone and cefixime. The genotypes were further correlated with their respective phenotypes for chloramphenicol, ampicillin, co-trimoxazole, ciprofloxacin and ceftriaxone. A high correlation was observed between genotypes and phenotypes in isolates of S. Typhi. The pan-genome analysis revealed that core genes were enriched in metabolic functions and accessory genes were majorly implicated in pathogenesis and antimicrobial resistance. The pan-genome of S. Typhi appears to be closed (B_pan  =  0.09) as analysed by Heap’s law. Simpson’s diversity index of 0.51 showed a lower level of genetic diversity among isolates of S. Typhi. Overall, this study augments the present knowledge that WGS can help predict resistance genotypes and eventual correlation with phenotypes, enabling the chance to spot AMR determinants for fast diagnosis and prioritize antibiotic use directly from sequence.

Dtar-Finder: program for drug target identification and characterization in bacteria

The drug target identification is the primary step for drug discovery. Recent development of computational techniques and availability of sequencing data has provided numerous opportunities for target identification but very few of them are fully automated. Here, we have developed a Perl program named Dtar-Finder for drug target identification and its characterization. Dtar-Finder predicts the drug targets which are essential to pathogen and non homologous to human, essential human anti-targets and gut microflora. This program is divided in 6 modules where modules 1-4 extract drug targets while module 5-6 predicts druggability and broad spectrum ability of identified candidates. The performance of this program in terms of sensitivity and specificity is calculated where specificity score was better compare to sensitivity score. Further, we have tested our script on C. botulinum (3572 proteins) and 35 potential drug targets have been identified. Out of which 16 broad spectrums candidates were predicted whereas 8 candidates are found to be druggable whiles remaining are considered to be 'novel'. These drug targets were cross-validated through literature showing 77.14% accuracy. Thus, the idea behind this work was to develop a fast, robust and generic program capable of finding drug targets in bacteria, which has been fulfilled satisfactorily.

Identification of potential drug targets and vaccine candidates in Clostridium botulinum using subtractive genomics approach

A subtractive genomic approach has been utilized for the identification of potential drug targets and vaccine candidates in Clostridium botulinum, the causative agent of flaccid paralysis in humans. The emergence of drug-resistant pathogenic strains has become a significant global public health threat. Treatment with antitoxin can target the neurotoxin at the extracellular level, however, can't converse the paralysis caused by botulism. Therefore, identification of drug targets and vaccine candidates in C. botulinum would be crucial to overcome drug resistance to existing antibiotic therapy. A total of 1729 crucial proteins, including chokepoint, virulence, plasmid and resistance proteins were mined and used for subtractive channel of analysis. This analysis disclosed 15 potential targets, which were non-similar to human, gut micro flora, and anti-targets in the host. The cellular localization of 6 targets was observed in the cytoplasm and might be used as a drug target, whereas 9 targets were localized in extracellular and membrane bound proteins and can be used as vaccine candidates. Furthermore, 4 targets were observed to be homologous to more than 75 pathogens and hence are considered as broad-spectrum antibiotic targets. The identified drug and vaccine targets in this study would be useful in the design and discovery of novel therapeutic compounds against botulism.