PE-only/PE_PGRS proteins of Mycobacterium tuberculosis contain a conserved tetra-peptide sequence DEVS/DXXS that is a potential caspase-3 cleavage motif

Mycobacterium tuberculosis PE_PGRS45 (Rv2615c) Promotes Recombinant Mycobacteria Intracellular Survival via Regulation of Innate Immunity, and Inhibition of Cell Apoptosis

Tuberculosis (TB), a bacterial infectious disease caused by Mycobacterium tuberculosis (M. tuberculosis), is a significant global public health problem. Mycobacterium tuberculosis expresses a unique family of PE_PGRS proteins that have been implicated in pathogenesis. Despite numerous studies, the functions of most PE_PGRS proteins in the pathogenesis of mycobacterium infections remain unclear. PE_PGRS45 (Rv2615c) is only found in pathogenic mycobacteria. In this study, we successfully constructed a recombinant Mycobacterium smegmatis (M. smegmatis) strain which heterologously expresses the PE_PGRS45 protein. We found that overexpression of this cell wall-associated protein enhanced bacterial viability under stress in vitro and cell survival in macrophages. MS_PE_PGRS45 decreased the secretion of pro-inflammatory cytokines such as IL-1β, IL-6, IL-12p40, and TNF-α. We also found that MS_PE_PGRS45 increased the expression of the anti-inflammatory cytokine IL-10 and altered macrophage-mediated immune responses. Furthermore, PE_PGRS45 enhanced the survival rate of M. smegmatis in macrophages by inhibiting cell apoptosis. Collectively, our findings show that PE_PGRS45 is a virulent factor actively involved in the interaction with the host macrophage.

Digerati - A multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins

The genome of Mycobacterium tuberculosis contains a relatively high percentage (10%) of genes that are poorly characterised because of their highly repetitive nature and high GC content. Some of these genes encode proteins of the PE/PPE family, which are thought to be involved in host-pathogen interactions, virulence, and disease pathogenicity. Members of this family are genetically divergent and challenging to both identify and classify using conventional computational tools. Thus, advanced in silico methods are needed to identify proteins of this family for subsequent functional annotation efficiently. In this study, we developed the first deep learning-based approach, termed Digerati, for the rapid and accurate identification of PE and PPE family proteins. Digerati was built upon a multipath parallel hybrid deep learning framework, which equips multi-layer convolutional neural networks with bidirectional, long short-term memory, equipped with a self-attention module to effectively learn the higher-order feature representations of PE/PPE proteins. Empirical studies demonstrated that Digerati achieved a significantly better performance (∼18-20%) than alignment-based approaches, including BLASTP, PHMMER, and HHsuite, in both prediction accuracy and speed. Digerati is anticipated to facilitate community-wide efforts to conduct high-throughput identification and analysis of PE/PPE family members. The webserver and source codes of Digerati are publicly available at http://web.unimelb-bioinfortools.cloud.edu.au/Digerati/.

Computational analysis and prediction of PE_PGRS proteins using machine learning

Mycobacterium tuberculosis genome comprises approximately 10% of two families of poorly characterised genes due to their high GC content and highly repetitive nature. The largest sub-group, the proline-glutamic acid polymorphic guanine-cytosine-rich sequence (PE_PGRS) family, is thought to be involved in host response and disease pathogenicity. Due to their high genetic variability and complexity of analysis, they are typically disregarded for further research in genomic studies. There are currently limited online resources and homology computational tools that can identify and analyse PE_PGRS proteins. In addition, they are computational-intensive and time-consuming, and lack sensitivity. Therefore, computational methods that can rapidly and accurately identify PE_PGRS proteins are valuable to facilitate the functional elucidation of the PE_PGRS family proteins. In this study, we developed the first machine learning-based bioinformatics approach, termed PEPPER, to allow users to identify PE_PGRS proteins rapidly and accurately. PEPPER was built upon a comprehensive evaluation of 13 popular machine learning algorithms with various sequence and physicochemical features. Empirical studies demonstrated that PEPPER achieved significantly better performance than alignment-based approaches, BLASTP and PHMMER, in both prediction accuracy and speed. PEPPER is anticipated to facilitate community-wide efforts to conduct high-throughput identification and analysis of PE_PGRS proteins.

Codon Optimization, Soluble Expression and Purification of PE_PGRS45 Gene from Mycobacterium tuberculosis and Preparation of Its Polyclonal Antibody Protein

Studies have demonstrated that PE_PGRS45 is constitutively expressed under various environmental conditions (such as nutrient depletion, hypoxia, and low pH) of the in vitro growth conditions examined, indicating that PE_PGRS45 protein is critical to the basic functions of Mycobacterium tuberculosis. However, there are few reports about the biochemical function and pathogenic mechanism of PE_PGRS45 protein. The fact that this M. tuberculosis gene is not easily expressed in E. coli may be mainly due to the high content of G+C and the use of unique codons. Fusion tags are indispensable tools used to improve the soluble expression of recombinant proteins and accelerate the characterization of protein structure and function. In the present study, His6, Trx, and His6-MBP were used as fusion tags, but only MBP-PE_PGRS45 was expressed solubly. The purification using His6-MBP tag-specific binding to the Ni column was easy to separate after the tag cleavage. We used the purified PE_PGRS45 to immunize New Zealand rabbits and obtained anti- PE_PGRS45 serum. We found that the titer of polyclonal antibodies against PE_PGR45 was higher than 1:256000. The result shows that purified PE_PGRS45 can induce New Zealand rabbits to produce high-titer antibodies. In conclusion, the recombinant protein PE_PGRS45 was successfully expressed in E. coli and specific antiserum was prepared, which will be followed by further evaluation of these specific antigens to develop highly sensitive and specific diagnostic tests for tuberculosis.

PE_PGRS: Vital proteins in promoting mycobacterial survival and modulating host immunity and metabolism

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M. tb), is the leading infectious cause of mortality worldwide. One of the key reasons for M. tb pathogenesis is the capability of M. tb to evade immune elimination and survive in macrophage, eventually causing chronic infection. However the pathogenicity mechanism of M. tb is not unclear yet, and thus diagnosis and therapy for TB remains a challenge. The genome of M. tb, encodes a unique protein family known as the PGRS family, with largely unexplored functions. Recently, an increasing number of reports have shown that the PE_PGRS proteins play critical roles in bacterial pathogenesis and immune evasion. The PE_PGRS protein family, characterized by a special N-terminal PE (Pro (P)-Glu (E) motif) domain and a C-terminal PGRS (Polymorphic GC-rich Repetitive Sequences) domain, is restricted mainly to pathogenic mycobacteria. Here we summarize current literature on the PE_PGRS as vital proteins in promoting bacterial survival and modulating host immunity, cell death and metabolism. We also highlight the potential of PE_PGRS as novel targets of anti-mycobacterial interventions for TB control.