The pangenome structure of human pathogen Mycobacterium kansasii

The non-tuberculous Mycobacterium kansasii, is the causative agent of destructive pulmonary and extrapulmonary infections in immunocompromised persons. Incessant use of multiple antibiotics and lack of effective vaccines did little to combat M. kansasii mediated infections. Here, a bioinformatic analysis has been carried out using PanExplorer, to analyze the pangenome aimed at functional characterization of the bacterium, understanding it’s pathogenic lifestyle and recognize the factors shaping evolution and variations amongst strains. M. kansasii had a large core genome (60.2%), a small (11.9%) dispensable genome and 27.9% strain-specific genes. The core genome of M. kansasii had a high concentration of COGs (Cluster of orthologous genes) linked to energy production and conversion, amino acid transport and metabolism, nucleotide transport and metabolism, coenzyme transport and metabolism, and secondary me-tabolite biosynthesis, transport and metabolism. Interestingly, numerous genes within the core and dispensable genome were associated with pathogenesis and virulence. Noteworthy among them were type VII secretion, ESX, PP and PPE family proteins. Although, M. kansasii genomes revealed overall relatedness and conservation, genomic rearrangements caused variability within the strains. The information from this analysis could assist future microbial genomics research on M. kansasii, and further studies, e.g., concerning distinctive gene clusters, and evolution

Understanding the nature and dynamics of Mycobacterium ulcerans cytochrome P450 monooxygenases (CYPs) - a bioinformatics approach

Cytochrome P450 monooxygenases (CYPs or P450s) are catalytically versatile hemoproteins, associated with drug metabolism, substrate utilization and pathogenesis. Mycobacterium ulcerans is a human pathogen causing Buruli ulcer. The study intended to investigate frequency and diversity of CYPs from M. ulcerans strains, understand the pan-CYPome clustering patterns and interconnection of CYPs using bioinformatics tools. M. ulcerans strains demonstrated the presence of 261 CYPs categorized into 35 families and 38 subfamilies. CYP138, CYP140, CYP189 and CYP125 were the flourishing families. Around, 20 CYP families and 20 subfamilies were conserved. Flourishing and conserved CYP families/subfamilies were associated with lipid metabolism, substrate utilization etc. CYP140 had a role in pathogenesis. CYP279 was the least dominant family. CYP135, CYP183, CYP190, CYP271 and CYP276 were diagnostic markers for M. ulcerans subsp. shinshuense strain ATCC 33728 and M. ulcerans strain P7741. The pan-CYPome specified that M. ulcerans is evolving by gaining CYPs. CYP centric clustering revealed diversity and resemblances among M. ulcerans strains. More diverse nature of the M. ulcerans strain Harvey could be attributed to its larger size and geographical location. Co-occurrence network demonstrated mutual associations amongst substantial number of CYP families/subfamilies. This work provided comprehensive understanding of previously unexplored CYPs from M. ulcerans

Comprehensive review of Mycobacterium ulcerans and Buruli ulcer from a bioinformatics perspective - what have we learnt?

Mycobacterium ulcerans is a non-tuberculous mycobacterium responsible for causing Buruli ulcer. This is a neglected tropical disease characterized by ulceration, necrotization and scarring of the soft tissues in human limbs. Pathogenesis of M. ulcerans is mediated by a cytotoxic and immunosuppressive compound called mycolactone. This steadily evolving mycobacteria has adapted itself with the aquatic insect ecosystem. Human communities in wetland ecosystems are prone to Buruli ulcer and several endemic regions have been identified. So far, there is no vaccine and surgery or prolonged treatment with antibiotic cocktail has been mandated to overcome resistance patterns. Application of bioinformatics tools in M. ulcerans and Buruli ulcer research during the post genomic era, has provided immense opportunities. In this review, we summarize the outcome of genome studies, comparative genomics, population genomics, genetic diversity analysis, phylogenetic studies and proteomics research pertaining to this disease. We also highlight the implications of in silico vaccine design and computational studies on natural products. Resultant findings are conducive for interpreting genome architecture, pathogenomic evolution and intraspecific divergence due to phylogeographic and virulence factors of M. ulcerans. Moreover, the outcome of population genomics studies in disease management, coupled with the efforts in discovering vaccine candidates and novel lead compounds, will enrich our understanding of Buruli ulcer

In silico immunoinformatics based prediction and designing of multi-epitope construct against human rhinovirus C

Human rhinovirus C (HRV-C) is an RNA virus infecting human respiratory tract. It is associated with complexities like asthma, chronic obstructive pulmonary disease, and respiratory damage. HRV-C has many serotypes. Till date there is no vaccine. Despite some limitations, corticosteroids, bronchodilators, and common cold medicines are used to treat HRV-C infections. Here, we have used immunoinformatics approach to predict suitable cytotoxic T-cell, helper T-cell and linear B-cell epitopes from the most antigenic protein. VP2 protein of Rhinovirus C53 strain USA/CO/2014-20993 was found to be most antigenic. The multi-epitope construct was designed using the best CTL, HTL and linear B-cell epitopes and attaching them with adjuvant and linkers. Interferon-gamma inducing epitopes and conformational B-cell epitopes were also predicted from the construct. Physicochemical and structural properties of the construct were satisfactory. Binding pockets were identified that could be the targets for designing effective inhibitors. Molecular docking revealed strong binding affinity of the construct with human Toll-like receptors 2 and 4. Normal mode analysis divulged stability of the docked complex. Codon optimization, in silico cloning and immune simulation analysis demonstrated suitability of the construct. These findings are likely to aid in vitro studies for developing vaccine against HRV-C

Understanding the bacteria in Mycobacterium avium complex (MAC) from a bioinformatic perspective - a review

Mycobacterium avium complex (MAC) houses a group of non-tuberculous mycobacteria causing pulmonary and disseminated infections. They are accountable for nodular bronchiectatic and fibrocavitary lung diseases in humans, Johne’s disease in ruminants, and respiratory diseases in birds. MAC infections pose challenges, owing to antibiotic resistance, prolonged therapy with antibiotic combinations, side effects, and risk of reinfections. Our objective was to summarize the outcome of computational research on the bacteria in MAC. This aimed to advance our understanding of characteristics, pathogenicity, and transmission dynamics to control infections. We incorporated information from the research on genomes, microbiomes, phylogeny, transcriptomes, proteomes, antibiotic resistance, and vaccine/drug target development to enhance our knowledge. It illuminated the significance of computational studies in distinguishing MAC species/subspecies and recognizing: virulence factors, lineage-specific markers, and transmission clusters. Moreover, it assisted in understanding: genomic diversity, resistance patterns, impact of polymorphisms in disease susceptibility, and taxa-induced dysbiosis in microbiomes. Additionally, this work highlighted the outcome of bioinformatic studies in predicting suitable vaccine epitopes, and novel drug targets to combat MAC infections. Bioinformatic research on bacteria within MAC has contributed to a deeper insight into the pathogens. These would facilitate better diagnosis, improved: therapeutic strategies, patient-specific surveillance, and community-level awareness

Draft Genome Sequence of Frankia sp. Strain BMG5.12, a Nitrogen-Fixing Actinobacterium Isolated from Tunisian Soils

Members of the actinomycete genus Frankia form a nitrogen-fixing symbiosis with 8 different families of actinorhizal plants. We report a draft genome sequence for Frankia sp. strain BMG5.12, a nitrogen-fixing actinobacterium isolated from Tunisian soils with the ability to infect Elaeagnus angustifolia and Myrica gale

Draft Genome Sequence of Frankia sp. Strain BCU110501, a Nitrogen-Fixing Actinobacterium Isolated from Nodules of Discaria trinevis

Frankia forms a nitrogen-fixing symbiosis with actinorhizal plants. We report a draft genome sequence for Frankia sp. strain BCU110501, a nitrogen-fixing actinobacterium isolated from nodules of Discaria trinevis grown in the Patagonia region of Argentina

Draft Genome Sequence of Frankia sp. Strain QA3, a Nitrogen-Fixing Actinobacterium Isolated from the Root Nodule of Alnus nitida

Members of the actinomycete genus Frankia form a nitrogen-fixing symbiosis with 8 different families of actinorhizal plants. We report a high-quality draft genome sequence for Frankia sp. strain QA3, a nitrogen-fixing actinobacterium isolated from root nodules of Alnus nitida

Draft Genome Sequence of Frankia sp. Strain CN3, an Atypical, Noninfective (Nod–) Ineffective (Fix–) Isolate from Coriaria nepalensis

We report here the genome sequence of Frankia sp. strain CN3, which was isolated from Coriaria nepalensis. This genome sequence is the first from the fourth lineage of Frankia, strains of which are unable to reinfect actinorhizal plants. At 10 Mb, it represents the largest Frankia genome sequenced to date

Recognition of microbial viability via TLR8 drives TFH cell differentiation and vaccine responses

Live attenuated vaccines are generally highly efficacious and often superior to inactivated vaccines, yet the underlying mechanisms of this remain largely unclear. Here we identify recognition of microbial viability as a potent stimulus for follicular helper T cell (TFH cell) differentiation and vaccine responses. Antigen-presenting cells (APCs) distinguished viable bacteria from dead bacteria through Toll-like receptor 8 (TLR8)-dependent detection of bacterial RNA. In contrast to dead bacteria and other TLR ligands, live bacteria, bacterial RNA and synthetic TLR8 agonists induced a specific cytokine profile in human and porcine APCs, thereby promoting TFH cell differentiation. In domestic pigs, immunization with a live bacterial vaccine induced robust TFH cell and antibody responses, but immunization with its heat-killed counterpart did not. Finally, a hypermorphic TLR8 polymorphism was associated with protective immunity elicited by vaccination with bacillus Calmette-Guérin (BCG) in a human cohort. We have thus identified TLR8 as an important driver of TFH cell differentiation and a promising target for TFH cell–skewing vaccine adjuvants