scholarly journals EvoMining reveals the origin and fate of natural products biosynthetic enzymes

2018 ◽  
Author(s):  
Nelly Sélem-Mojica ◽  
César Aguilar ◽  
Karina Gutiérrez-García ◽  
Christian E. Martínez-Guerrero ◽  
Francisco Barona-Gómez
Keyword(s):  
Natural Products ◽  
Evolutionary Dynamics ◽  
Sequence Similarity ◽  
Genome Mining ◽  
Gene Clusters ◽  
Lessons Learned ◽  
Metabolic Enzyme ◽  
Link Type ◽  
A Genome ◽  
Enzyme Families

ABSTRACTNatural products, or specialized metabolites, are important for medicine and agriculture alike, as well as for the fitness of the organisms that produce them. Microbial genome mining aims at extracting metabolic information from genomes of microbes presumed to produce these compounds. Typically, canonical enzyme sequences from known biosynthetic systems are identified after sequence similarity searches. Despite this being an efficient process the likelihood of identifying truly novel biosynthetic systems is low. To overcome this limitation we previously introduced EvoMining, a genome mining approach that incorporates evolutionary principles. Here, we release and use our latest version of EvoMining, which includes novel visualization features and customizable databases, to analyze 42 central metabolic enzyme families conserved throughout Actinobacteria, Cyanobacteria, Pseudomonas and Archaea. We found that expansion-and-recruitment profiles of these enzyme families are lineage specific, opening a new metabolic space related to ‘shell’ enzymes, which have been overlooked to date. As a case study of canonical shell enzymes, we characterized the expansion and recruitment of glutamate dehydrogenase and acetolactate synthase into scytonemin biosynthesis, and into other central metabolic pathways driving microbial adaptive evolution. By defining the origins and fates of metabolic enzymes, EvoMining not only complements traditional genome mining approaches as an unbiased and rule-independent strategy, but it opens the door to gain insights into the evolution of natural products biosynthesis. We anticipate that EvoMining will be broadly used for metabolic evolutionary studies, and to generate genome-mining predictions leading to unprecedented chemical scaffolds and new antibiotics.DATA SUMMARYDatabases have been deposited at Zenodo; DOI: 10.5281/zenodo.1162336 http://zenodo.org/deposit/1219709Trees and metadata have been deposited in MicroReactGDH Actinobacteria https://microreact.org/project/r1IhjVm6XGDH Cyanobacteria https://microreact.org/project/HyjYUN7pQ)GDH Pseudomonas https://microreact.org/project/rJPC4EQa7GDH Archaea https://microreact.org/project/ByUcvNmaXALS Cyanobacteria https://microreact.org/project/B11HkUtdmEvoMining code has been deposited in gitHub https://github/nselem/evominingDocker container in Dockerhub https://hub.docker.com/r/nselem/evomining/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.IMPACT STATEMENTEvoMining allows studying expansion-and-recruitment events of enzyme families in prokaryotic lineages, with the goal of providing both evolutionary insights and a genome mining approach for the discovery of truly novel natural products biosynthetic gene clusters. Thus, by better understanding the origin and fate of gene copies within enzyme families, this work contributes towards the identification of lineage-dependent enzymes that we call ‘shell’ enzymes, which are ideal beacons to unveil ‘chemical dark matter’. We show that enzyme functionality is a continuum, including transition enzymes located between central and specialized metabolism. To exemplify these evolutionary dynamics, we focused in the genes directing the synthesis of the sunscreen peptide scytonemin, as the two key enzymes of this biosynthetic pathway behave as shell enzymes and were correctly identified by EvoMining. We also show how evolutionary approaches are better suited to study unexplored lineages, such as those belonging to the Archaea domain, which is systematically mined here for novel natural products for the first time. The release of EvoMining as a stand-alone tool will allow researchers to explore its own enzyme families of interest, within their own genomic lineages of expertise, by taking into account the lessons learned from this work

scholarly journals Integration of machine learning and pan-genomics expands the biosynthetic landscape of RiPP natural products

2020 ◽  
Author(s):  
Alexander M. Kloosterman ◽  
Peter Cimermancic ◽  
Somayah S. Elsayed ◽  
Chao Du ◽  
Michalis Hadjithomas ◽  
...  
Keyword(s):  
Natural Products ◽  
Sequence Similarity ◽  
Genome Mining ◽  
Gene Clusters ◽  
Data Availability ◽  
Training Data ◽  
Support Vector ◽  
Product Families ◽  
Link Type ◽  
Clinical Drugs

AbstractMost clinical drugs are based on microbial natural products, with compound classes including polyketides (PKS), non-ribosomal peptides (NRPS), fluoroquinones and ribosomally synthesized and post-translationally modified peptides (RiPPs). While variants of biosynthetic gene clusters (BGCs) for known classes of natural products are easy to identify in genome sequences, BGCs for new compound classes escape attention. In particular, evidence is accumulating that for RiPPs, subclasses known thus far may only represent the tip of an iceberg. Here, we present decRiPPter (Data-driven Exploratory Class-independent RiPP TrackER), a RiPP genome mining algorithm aimed at the discovery of novel RiPP classes. DecRiPPter combines a Support Vector Machine (SVM) that identifies candidate RiPP precursors with pan-genomic analyses to identify which of these are encoded within operon-like structures that are part of the accessory genome of a genus. Subsequently, it prioritizes such regions based on the presence of new enzymology and based on patterns of gene cluster and precursor peptide conservation across species. We then applied decRiPPter to mine 1,295 Streptomyces genomes, which led to the identification of 42 new candidate RiPP families that could not be found by existing programs. One of these was studied further and elucidated as a novel subfamily of lanthipeptides, designated Class V. Two previously unidentified modifying enzymes are proposed to create the hallmark lanthionine bridges. Taken together, our work highlights how novel natural product families can be discovered by methods going beyond sequence similarity searches to integrate multiple pathway discovery criteria.Code and data availabilityThe source code of DecRiPPter is freely available online at https://github.com/Alexamk/decRiPPter. Results of the data analysis are available online at http://www.bioinformatics.nl/~medem005/decRiPPter_strict/index.html and http://www.bioinformatics.nl/~medem005/decRiPPter_mild/index.html (for the strict and mild filters, respectively). All training data and code used to generate these, as well as outputs of the data analyses, are available on Zenodo at doi:10.5281/zenodo.3834818.

scholarly journals Activation and enhancement of Caerulomycin A biosynthesis in marine-derived Actinoalloteichus sp. AHMU CJ021 by combinatorial genome mining strategies

2020 ◽  
Author(s):  
Yunchang Xie ◽  
Jiawen Chen ◽  
Bo Wang ◽  
Tai Chen ◽  
Junyu Chen ◽  
...  
Keyword(s):  
Natural Products ◽  
Mutant Strain ◽  
Genome Mining ◽  
Gene Clusters ◽  
Immunosuppressive Drug ◽  
Biosynthetic Gene ◽  
Bioactive Natural Products ◽  
Drug Lead ◽  
A Genome ◽  
Mining Work

Abstract Backgrounds: Activation of silent biosynthetic gene clusters (BGCs) in marine-derived actinomycete strains is a feasible strategy to discover bioactive natural products. Actinoalloteichus sp. AHMU CJ021, isolated from the seashore, was shown to contain an intact but silent caerulomycin A (CRM A) BGC-cam in its genome. Thus, a genome mining work was preformed to activate the strain’s bioproduction of CRM A, an immunosuppressive drug lead with diverse bioactivities.Results: To well activate the expression of cam, ribosomal engineering was adopted to treat the wild type Actinoalloteichus sp. AHMU CJ021. The initial mutant strain XC-11G with gentamycin resistance and CRM A bioproduction titer of 42.51 ± 4.22 mg/L was selected from all generated mutant strains by gene expression comparison of the essential biosynthetic gene-camE. The titer of CRM A bioproduction was then improved by two strain breeding methods via UV mutagenesis and cofactor engineering-directed increasing of intracellular riboflavin, which finally generated the optimal mutant strain XC-11GUR with a CRM A bioproduction titer of 113.91 ± 7.58 mg/L. Subsequently, this titer of strain XC-11GUR was improved to 618.61 ± 16.29 mg/L through medium optimization together with further adjustment derived from response surface methodology. In terms of this 14.7 folds increase in the titer of CRM A compared to the initial value, strain XC-GUR could be a well alternative strain for CRM A development.Conclusions: Our results have constructed an ideal CRM A producer. More importantly, our efforts also have demonstrated the effectiveness of abovementioned combinatorial strategies, which is applicable to the genome mining of bioactive natural products from abundant actinomycetes strains.

scholarly journals Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters

2017 ◽  
Vol 20 (4) ◽  
pp. 1103-1113 ◽  
Author(s):  
Kai Blin ◽  
Hyun Uk Kim ◽  
Marnix H Medema ◽  
Tilmann Weber
Keyword(s):  
Natural Products ◽  
Small Molecules ◽  
Sequence Similarity ◽  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Rule Based ◽  
Chemical Structures ◽  
Annotation Quality

Abstract Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats such as rule-based BGC detection, sequence and annotation quality and cluster boundary prediction, which all have to be considered while planning for, performing and analyzing the results of genome mining studies.

scholarly journals Expansion of RiPP biosynthetic space through integration of pan-genomics and machine learning uncovers a novel class of lanthipeptides

PLoS Biology ◽  
2020 ◽  
Vol 18 (12) ◽  
pp. e3001026
Author(s):  
Alexander M. Kloosterman ◽  
Peter Cimermancic ◽  
Somayah S. Elsayed ◽  
Chao Du ◽  
Michalis Hadjithomas ◽  
...  
Keyword(s):  
Natural Products ◽  
Natural Product ◽  
Sequence Similarity ◽  
Genome Mining ◽  
Gene Clusters ◽  
Support Vector ◽  
Chemical Labeling ◽  
Product Families ◽  
Anticancer Properties ◽  
Modified Peptides

Microbial natural products constitute a wide variety of chemical compounds, many which can have antibiotic, antiviral, or anticancer properties that make them interesting for clinical purposes. Natural product classes include polyketides (PKs), nonribosomal peptides (NRPs), and ribosomally synthesized and post-translationally modified peptides (RiPPs). While variants of biosynthetic gene clusters (BGCs) for known classes of natural products are easy to identify in genome sequences, BGCs for new compound classes escape attention. In particular, evidence is accumulating that for RiPPs, subclasses known thus far may only represent the tip of an iceberg. Here, we present decRiPPter (Data-driven Exploratory Class-independent RiPP TrackER), a RiPP genome mining algorithm aimed at the discovery of novel RiPP classes. DecRiPPter combines a Support Vector Machine (SVM) that identifies candidate RiPP precursors with pan-genomic analyses to identify which of these are encoded within operon-like structures that are part of the accessory genome of a genus. Subsequently, it prioritizes such regions based on the presence of new enzymology and based on patterns of gene cluster and precursor peptide conservation across species. We then applied decRiPPter to mine 1,295 Streptomyces genomes, which led to the identification of 42 new candidate RiPP families that could not be found by existing programs. One of these was studied further and elucidated as a representative of a novel subfamily of lanthipeptides, which we designate class V. The 2D structure of the new RiPP, which we name pristinin A3 (1), was solved using nuclear magnetic resonance (NMR), tandem mass spectrometry (MS/MS) data, and chemical labeling. Two previously unidentified modifying enzymes are proposed to create the hallmark lanthionine bridges. Taken together, our work highlights how novel natural product families can be discovered by methods going beyond sequence similarity searches to integrate multiple pathway discovery criteria.

scholarly journals Activation and enhancement of Caerulomycin A biosynthesis in marine-derived Actinoalloteichus sp. AHMU CJ021 by combinatorial genome mining strategies

2020 ◽  
Author(s):  
Yunchang Xie ◽  
Jiawen Chen ◽  
Bo Wang ◽  
Tai Chen ◽  
Junyu Chen ◽  
...  
Keyword(s):  
Natural Products ◽  
Mutant Strain ◽  
Genome Mining ◽  
Gene Clusters ◽  
Immunosuppressive Drug ◽  
Biosynthetic Gene ◽  
Bioactive Natural Products ◽  
Drug Lead ◽  
A Genome ◽  
Mining Work

Abstract Backgrounds: Activation of silent biosynthetic gene clusters (BGCs) in marine-derived actinomycete strains is a feasible strategy to discover bioactive natural products. Actinoalloteichus sp. AHMU CJ021, isolated from the seashore, was shown to contain an intact but silent caerulomycin A (CRM A) BGC-cam in its genome. Thus, a genome mining work was preformed to activate the strain’s production of CRM A, an immunosuppressive drug lead with diverse bioactivities.Results: To well activate the expression of cam, ribosome engineering was adopted to treat the wild type Actinoalloteichus sp. AHMU CJ021. The initial mutant strain XC-11G with gentamycin resistance and CRM A production titer of 42.51 ± 4.22 mg/L was selected from all generated mutant strains by gene expression comparison of the essential biosynthetic gene-camE. The titer of CRM A production was then improved by two strain breeding methods via UV mutagenesis and cofactor engineering-directed increase of intracellular riboflavin, which finally generated the optimal mutant strain XC-11GUR with a CRM A production titer of 113.91 ± 7.58 mg/L. Subsequently, this titer of strain XC-11GUR was improved to 618.61 ± 16.29 mg/L through medium optimization together with further adjustment derived from response surface methodology. In terms of this 14.6 folds increase in the titer of CRM A compared to the initial value, strain XC-GUR could be a well alternative strain for CRM A development.Conclusions: Our results have constructed an ideal CRM A producer. More importantly, our efforts also have demonstrated the effectiveness of abovementioned combinatorial strategies, which is applicable to the genome mining of bioactive natural products from abundant actinomycetes strains.

scholarly journals Activation and enhancement of Caerulomycin A biosynthesis in marine-derived Actinoalloteichus sp. AHMU CJ021 by combinatorial genome mining strategies

2020 ◽  
Author(s):  
Yunchang Xie ◽  
Jiawen Chen ◽  
Bo Wang ◽  
Tai Chen ◽  
Junyu Chen ◽  
...  
Keyword(s):  
Natural Products ◽  
Mutant Strain ◽  
Genome Mining ◽  
Gene Clusters ◽  
Immunosuppressive Drug ◽  
Biosynthetic Gene ◽  
Bioactive Natural Products ◽  
Drug Lead ◽  
A Genome ◽  
Mining Work

Abstract Backgrounds: Activation of silent biosynthetic gene clusters (BGCs) in marine-derived actinomycete strains is a feasible strategy to discover bioactive natural products. Actinoalloteichus sp. AHMU CJ021, isolated from the seashore, was shown to contain an intact but silent caerulomycin A (CRM A) BGC- cam in its genome. Thus, a genome mining work was preformed to activate the strain’s production of CRM A, an immunosuppressive drug lead with diverse bioactivities.Results: To well activate the expression of cam , ribosome engineering was adopted to treat the wild type Actinoalloteichus sp. AHMU CJ021. The initial mutant strain XC-11G with gentamycin resistance and CRM A production titer of 42.51 ± 4.22 mg/L was selected from all generated mutant strains by gene expression comparison of the essential biosynthetic gene-camE. The titer of CRM A production was then improved by two strain breeding methods via UV mutagenesis and cofactor engineering-directed increase of intracellular riboflavin, which finally generated the optimal mutant strain XC-11GUR with a CRM A production titer of 113.91 ± 7.58 mg/L. Subsequently, this titer of strain XC-11GUR was improved to 618.61 ± 16.29 mg/L through medium optimization together with further adjustment derived from response surface methodology. In terms of this 14.6 folds increase in the titer of CRM A compared to the initial value, strain XC-GUR could be a well alternative strain for CRM A development.Conclusions: Our results have constructed an ideal CRM A producer. More importantly, our efforts also have demonstrated the effectiveness of abovementioned combinatorial strategies, which is applicable to the genome mining of bioactive natural products from abundant actinomycetes strains.

scholarly journals Identification of a Tambjamine Gene Cluster in Streptomyces Reveals Convergent Evolution of the Biosynthetic Pathway

2020 ◽  
Author(s):  
Neil L Grenade ◽  
Dragos S. Chiriac ◽  
Graeme W. Howe ◽  
Avena Ross
Keyword(s):  
Natural Products ◽  
De Novo ◽  
Sequence Similarity ◽  
Genome Mining ◽  
Gene Clusters ◽  
Primary Metabolism ◽  
Biosynthetic Gene Clusters ◽  
Microbial Genomes ◽  
Sequence Similarity Networks ◽  
Related Compounds

Bacterial natural products are an immensely valuable source of therapeutics. As modern DNA sequencing efforts provide increasing numbers of microbial genomes, it is clear that the molecules produced by most natural product biosynthetic gene clusters (BGCs) remain unknown. Genome mining makes use of bioinformatic techniques to elucidate the natural products produced by these “orphan” BGCs. Here, we report the use of sequence similarity networks (SSNs) and genome neighborhood networks (GNNs) to identify an orphan BGC that is responsible for the production of the antitumor tambjamine BE-18591 in Streptomyces albus NRRL B-2362. Although BE-18591 is a close structural analogue of tambjamine YP1 produced by Pseudoalteromonas tunicata, the biosynthetic routes to produce these molecules differ significantly. Notably, the C12-alkylamine tail that is appended onto the bipyrrole core of tambjamine YP1 is derived from fatty acids siphoned from the primary metabolism of the pseudoalteromonad, whilst the S. albus NRRL B-2362 BGC encodes a dedicated system for the de novo biosynthesis of the alkylamine portion of tambjamine BE-18591. These remarkably different biosynthetic strategies represent a striking example of convergent BGC evolution, with selective pressure for the production of tambjamines seemingly leading to the emergence of separate biosynthetic pathways in pseudoalteromonads and streptomycetes that ultimately produce closely related compounds

scholarly journals Activation and enhancement of caerulomycin A biosynthesis in marine-derived Actinoalloteichus sp. AHMU CJ021 by combinatorial genome mining strategies

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Yunchang Xie ◽  
Jiawen Chen ◽  
Bo Wang ◽  
Tai Chen ◽  
Junyu Chen ◽  
...  
Keyword(s):  
Natural Products ◽  
Mutant Strain ◽  
Genome Mining ◽  
Gene Clusters ◽  
Immunosuppressive Drug ◽  
Biosynthetic Gene ◽  
Bioactive Natural Products ◽  
Drug Lead ◽  
A Genome ◽  
Mining Work

Abstract Background Activation of silent biosynthetic gene clusters (BGCs) in marine-derived actinomycete strains is a feasible strategy to discover bioactive natural products. Actinoalloteichus sp. AHMU CJ021, isolated from the seashore, was shown to contain an intact but silent caerulomycin A (CRM A) BGC-cam in its genome. Thus, a genome mining work was preformed to activate the strain’s production of CRM A, an immunosuppressive drug lead with diverse bioactivities. Results To well activate the expression of cam, ribosome engineering was adopted to treat the wild type Actinoalloteichus sp. AHMU CJ021. The initial mutant strain XC-11G with gentamycin resistance and CRM A production titer of 42.51 ± 4.22 mg/L was selected from all generated mutant strains by gene expression comparison of the essential biosynthetic gene-camE. The titer of CRM A production was then improved by two strain breeding methods via UV mutagenesis and cofactor engineering-directed increase of intracellular riboflavin, which finally generated the optimal mutant strain XC-11GUR with a CRM A production titer of 113.91 ± 7.58 mg/L. Subsequently, this titer of strain XC-11GUR was improved to 618.61 ± 16.29 mg/L through medium optimization together with further adjustment derived from response surface methodology. In terms of this 14.6 folds increase in the titer of CRM A compared to the initial value, strain XC-GUR could be a well alternative strain for CRM A development. Conclusions Our results had constructed an ideal CRM A producer. More importantly, our efforts also had demonstrated the effectiveness of abovementioned combinatorial strategies, which is applicable to the genome mining of bioactive natural products from abundant actinomycetes strains.

scholarly journals Identification of a Tambjamine Gene Cluster in Streptomyces Reveals Convergent Evolution of the Biosynthetic Pathway

2020 ◽  
Author(s):  
Neil L Grenade ◽  
Dragos S. Chiriac ◽  
Graeme W. Howe ◽  
Avena Ross
Keyword(s):  
Natural Products ◽  
De Novo ◽  
Sequence Similarity ◽  
Genome Mining ◽  
Gene Clusters ◽  
Primary Metabolism ◽  
Biosynthetic Gene Clusters ◽  
Microbial Genomes ◽  
Sequence Similarity Networks ◽  
Related Compounds

Bacterial natural products are an immensely valuable source of therapeutics. As modern DNA sequencing efforts provide increasing numbers of microbial genomes, it is clear that the molecules produced by most natural product biosynthetic gene clusters (BGCs) remain unknown. Genome mining makes use of bioinformatic techniques to elucidate the natural products produced by these “orphan” BGCs. Here, we report the use of sequence similarity networks (SSNs) and genome neighborhood networks (GNNs) to identify an orphan BGC that is responsible for the production of the antitumor tambjamine BE-18591 in Streptomyces albus NRRL B-2362. Although BE-18591 is a close structural analogue of tambjamine YP1 produced by Pseudoalteromonas tunicata, the biosynthetic routes to produce these molecules differ significantly. Notably, the C12-alkylamine tail that is appended onto the bipyrrole core of tambjamine YP1 is derived from fatty acids siphoned from the primary metabolism of the pseudoalteromonad, whilst the S. albus NRRL B-2362 BGC encodes a dedicated system for the de novo biosynthesis of the alkylamine portion of tambjamine BE-18591. These remarkably different biosynthetic strategies represent a striking example of convergent BGC evolution, with selective pressure for the production of tambjamines seemingly leading to the emergence of separate biosynthetic pathways in pseudoalteromonads and streptomycetes that ultimately produce closely related compounds

scholarly journals Phylogenetic distribution and evolutionary dynamics of nod and T3SS genes in the genus Bradyrhizobium

2020 ◽  
Vol 6 (9) ◽  
Author(s):  
Albin Teulet ◽  
Djamel Gully ◽  
Zoe Rouy ◽  
Alicia Camuel ◽  
Ralf Koebnik ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Sequence Similarity ◽  
Gene Clusters ◽  
Effector Proteins ◽  
Secretion Systems ◽  
Genome Sequences ◽  
Content Type ◽  
Link Type ◽  
Sumo Proteases ◽  
Genes Encoding

Bradyrhizobium are abundant soil bacteria and the major symbiont of legumes. The recent availability of Bradyrhizobium genome sequences provides a large source of information for analysis of symbiotic traits. In this study, we investigated the evolutionary dynamics of the nodulation genes (nod) and their relationship with the genes encoding type III secretion systems (T3SS) and their effectors among bradyrhizobia. Based on the comparative analysis of 146 Bradyrhizobium genome sequences, we identified six different types of T3SS gene clusters. The two predominant cluster types are designated RhcIa and RhcIb and both belong to the RhcI-T3SS family previously described in other rhizobia. They are found in 92/146 strains, most of them also containing nod genes. RhcIa and RhcIb gene clusters differ in the genes they carry: while the translocon-encoding gene nopX is systematically found in strains containing RhcIb, the nopE and nopH genes are specifically conserved in strains containing RhcIa, suggesting that these last two genes might functionally substitute nopX and play a role related to effector translocation. Phylogenetic analysis suggests that bradyrhizobia simultaneously gained nod and RhcI-T3SS gene clusters via horizontal transfer or subsequent vertical inheritance of a symbiotic island containing both. Sequence similarity searches for known Nop effector proteins in bradyrhizobial proteomes revealed the absence of a so-called core effectome, i.e. that no effector is conserved among all Bradyrhizobium strains. However, NopM and SUMO proteases were found to be the main effector families, being represented in the majority of the genus. This study indicates that bradyrhizobial T3SSs might play a more significant symbiotic role than previously thought and provides new candidates among T3SS structural proteins and effectors for future functional investigations.

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