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Gemler BT, Mukherjee C, Howland CA, Huk D, Shank Z, Harbo LJ, Tabbaa OP, Bartling CM. Function-based classification of hazardous biological sequences: Demonstration of a new paradigm for biohazard assessments. Front Bioeng Biotechnol 2022; 10:979497. [PMID: 36277394 PMCID: PMC9585941 DOI: 10.3389/fbioe.2022.979497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 08/31/2022] [Indexed: 12/04/2022] Open
Abstract
Bioengineering applies analytical and engineering principles to identify functional biological building blocks for biotechnology applications. While these building blocks are leveraged to improve the human condition, the lack of simplistic, machine-readable definition of biohazards at the function level is creating a gap for biosafety practices. More specifically, traditional safety practices focus on the biohazards of known pathogens at the organism-level and may not accurately consider novel biodesigns with engineered functionalities at the genetic component-level. This gap is motivating the need for a paradigm shift from organism-centric procedures to function-centric biohazard identification and classification practices. To address this challenge, we present a novel methodology for classifying biohazards at the individual sequence level, which we then compiled to distinguish the biohazardous property of pathogenicity at the whole genome level. Our methodology is rooted in compilation of hazardous functions, defined as a set of sequences and associated metadata that describe coarse-level functions associated with pathogens (e.g., adherence, immune subversion). We demonstrate that the resulting database can be used to develop hazardous “fingerprints” based on the functional metadata categories. We verified that these hazardous functions are found at higher levels in pathogens compared to non-pathogens, and hierarchical clustering of the fingerprints can distinguish between these two groups. The methodology presented here defines the hazardous functions associated with bioengineering functional building blocks at the sequence level, which provide a foundational framework for classifying biological hazards at the organism level, thus leading to the improvement and standardization of current biosecurity and biosafety practices.
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Wallqvist A, Wang H, Zavaljevski N, Memišević V, Kwon K, Pieper R, Rajagopala SV, Reifman J. Mechanisms of action of Coxiella burnetii effectors inferred from host-pathogen protein interactions. PLoS One 2017; 12:e0188071. [PMID: 29176882 PMCID: PMC5703456 DOI: 10.1371/journal.pone.0188071] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 10/31/2017] [Indexed: 02/06/2023] Open
Abstract
Coxiella burnetii is an obligate Gram-negative intracellular pathogen and the etiological agent of Q fever. Successful infection requires a functional Type IV secretion system, which translocates more than 100 effector proteins into the host cytosol to establish the infection, restructure the intracellular host environment, and create a parasitophorous vacuole where the replicating bacteria reside. We used yeast two-hybrid (Y2H) screening of 33 selected C. burnetii effectors against whole genome human and murine proteome libraries to generate a map of potential host-pathogen protein-protein interactions (PPIs). We detected 273 unique interactions between 20 pathogen and 247 human proteins, and 157 between 17 pathogen and 137 murine proteins. We used orthology to combine the data and create a single host-pathogen interaction network containing 415 unique interactions between 25 C. burnetii and 363 human proteins. We further performed complementary pairwise Y2H testing of 43 out of 91 C. burnetii-human interactions involving five pathogen proteins. We used the combined data to 1) perform enrichment analyses of target host cellular processes and pathways, 2) examine effectors with known infection phenotypes, and 3) infer potential mechanisms of action for four effectors with uncharacterized functions. The host-pathogen interaction profiles supported known Coxiella phenotypes, such as adapting cell morphology through cytoskeletal re-arrangements, protein processing and trafficking, organelle generation, cholesterol processing, innate immune modulation, and interactions with the ubiquitin and proteasome pathways. The generated dataset of PPIs-the largest collection of unbiased Coxiella host-pathogen interactions to date-represents a rich source of information with respect to secreted pathogen effector proteins and their interactions with human host proteins.
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Affiliation(s)
- Anders Wallqvist
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Hao Wang
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Nela Zavaljevski
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Vesna Memišević
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Keehwan Kwon
- J. Craig Venter Institute, Rockville, Maryland, United States of America
| | - Rembert Pieper
- J. Craig Venter Institute, Rockville, Maryland, United States of America
| | | | - Jaques Reifman
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
- * E-mail:
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Lien YW, Lai EM. Type VI Secretion Effectors: Methodologies and Biology. Front Cell Infect Microbiol 2017; 7:254. [PMID: 28664151 PMCID: PMC5471719 DOI: 10.3389/fcimb.2017.00254] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Accepted: 05/31/2017] [Indexed: 12/26/2022] Open
Abstract
The type VI secretion system (T6SS) is a nanomachine deployed by many Gram-negative bacteria as a weapon against eukaryotic hosts or prokaryotic competitors. It assembles into a bacteriophage tail-like structure that can transport effector proteins into the environment or target cells for competitive survival or pathogenesis. T6SS effectors have been identified by a variety of approaches, including knowledge/hypothesis-dependent and discovery-driven approaches. Here, we review and discuss the methods that have been used to identify T6SS effectors and the biological and biochemical functions of known effectors. On the basis of the nature and transport mechanisms of T6SS effectors, we further propose potential strategies that may be applicable to identify new T6SS effectors.
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Affiliation(s)
- Yun-Wei Lien
- Institute of Plant and Microbial Biology, Academia SinicaTaipei, Taiwan.,Department of Plant Pathology and Microbiology, National Taiwan UniversityTaipei, Taiwan
| | - Erh-Min Lai
- Institute of Plant and Microbial Biology, Academia SinicaTaipei, Taiwan.,Department of Plant Pathology and Microbiology, National Taiwan UniversityTaipei, Taiwan
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Memišević V, Kumar K, Zavaljevski N, DeShazer D, Wallqvist A, Reifman J. DBSecSys 2.0: a database of Burkholderia mallei and Burkholderia pseudomallei secretion systems. BMC Bioinformatics 2016; 17:387. [PMID: 27650316 PMCID: PMC5029111 DOI: 10.1186/s12859-016-1242-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 09/08/2016] [Indexed: 01/08/2023] Open
Abstract
Background Burkholderia mallei and B. pseudomallei are the causative agents of glanders and melioidosis, respectively, diseases with high morbidity and mortality rates. B. mallei and B. pseudomallei are closely related genetically; B. mallei evolved from an ancestral strain of B. pseudomallei by genome reduction and adaptation to an obligate intracellular lifestyle. Although these two bacteria cause different diseases, they share multiple virulence factors, including bacterial secretion systems, which represent key components of bacterial pathogenicity. Despite recent progress, the secretion system proteins for B. mallei and B. pseudomallei, their pathogenic mechanisms of action, and host factors are not well characterized. Results We previously developed a manually curated database, DBSecSys, of bacterial secretion system proteins for B. mallei. Here, we report an expansion of the database with corresponding information about B. pseudomallei. DBSecSys 2.0 contains comprehensive literature-based and computationally derived information about B. mallei ATCC 23344 and literature-based and computationally derived information about B. pseudomallei K96243. The database contains updated information for 163 B. mallei proteins from the previous database and 61 additional B. mallei proteins, and new information for 281 B. pseudomallei proteins associated with 5 secretion systems, their 1,633 human- and murine-interacting targets, and 2,400 host-B. mallei interactions and 2,286 host-B. pseudomallei interactions. The database also includes information about 13 pathogenic mechanisms of action for B. mallei and B. pseudomallei secretion system proteins inferred from the available literature or computationally. Additionally, DBSecSys 2.0 provides details about 82 virulence attenuation experiments for 52 B. mallei secretion system proteins and 98 virulence attenuation experiments for 61 B. pseudomallei secretion system proteins. We updated the Web interface and data access layer to speed-up users’ search of detailed information for orthologous proteins related to secretion systems of the two pathogens. Conclusions The updates of DBSecSys 2.0 provide unique capabilities to access comprehensive information about secretion systems of B. mallei and B. pseudomallei. They enable studies and comparisons of corresponding proteins of these two closely related pathogens and their host-interacting partners. The database is available at http://dbsecsys.bhsai.org.
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Affiliation(s)
- Vesna Memišević
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA
| | - Kamal Kumar
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA
| | - Nela Zavaljevski
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA
| | - David DeShazer
- Bacteriology Division, U.S. Army Medical Research Institute of Infectious Diseases, Fort Detrick, MD 21702, USA
| | - Anders Wallqvist
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA
| | - Jaques Reifman
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA.
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Bozue JA, Chaudhury S, Amemiya K, Chua J, Cote CK, Toothman RG, Dankmeyer JL, Klimko CP, Wilhelmsen CL, Raymond JW, Zavaljevski N, Reifman J, Wallqvist A. Phenotypic Characterization of a Novel Virulence-Factor Deletion Strain of Burkholderia mallei That Provides Partial Protection against Inhalational Glanders in Mice. Front Cell Infect Microbiol 2016; 6:21. [PMID: 26955620 PMCID: PMC4767903 DOI: 10.3389/fcimb.2016.00021] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Accepted: 02/01/2016] [Indexed: 01/29/2023] Open
Abstract
Burkholderia mallei (Bm) is a highly infectious intracellular pathogen classified as a category B biological agent by the Centers for Disease Control and Prevention. After respiratory exposure, Bm establishes itself within host macrophages before spreading into major organ systems, which can lead to chronic infection, sepsis, and death. Previously, we combined computational prediction of host-pathogen interactions with yeast two-hybrid experiments and identified novel virulence factor genes in Bm, including BMAA0553, BMAA0728 (tssN), and BMAA1865. In the present study, we used recombinant allelic exchange to construct deletion mutants of BMAA0553 and tssN (ΔBMAA0553 and ΔTssN, respectively) and showed that both deletions completely abrogated virulence at doses of >100 times the LD50 of the wild-type Bm strain. Analysis of ΔBMAA0553- and ΔTssN-infected mice showed starkly reduced bacterial dissemination relative to wild-type Bm, and subsequent in vitro experiments characterized pathogenic phenotypes with respect to intracellular growth, macrophage uptake and phagosomal escape, actin-based motility, and multinucleated giant cell formation. Based on observed in vitro and in vivo phenotypes, we explored the use of ΔTssN as a candidate live-attenuated vaccine. Mice immunized with aerosolized ΔTssN showed a 21-day survival rate of 67% after a high-dose aerosol challenge with the wild-type Bm ATCC 23344 strain, compared to a 0% survival rate for unvaccinated mice. However, analysis of histopathology and bacterial burden showed that while the surviving vaccinated mice were protected from acute infection, Bm was still able to establish a chronic infection. Vaccinated mice showed a modest IgG response, suggesting a limited potential of ΔTssN as a vaccine candidate, but also showed prolonged elevation of pro-inflammatory cytokines, underscoring the role of cellular and innate immunity in mitigating acute infection in inhalational glanders.
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Affiliation(s)
- Joel A Bozue
- Bacteriology Division, United States Army Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Sidhartha Chaudhury
- Telemedicine and Advanced Technology Research Center, Biotechnology HPC Software Applications Institute, United States Army Medical Research and Materiel Command Fort Detrick, MD, USA
| | - Kei Amemiya
- Bacteriology Division, United States Army Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Jennifer Chua
- Bacteriology Division, United States Army Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Christopher K Cote
- Bacteriology Division, United States Army Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Ronald G Toothman
- Bacteriology Division, United States Army Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Jennifer L Dankmeyer
- Bacteriology Division, United States Army Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Christopher P Klimko
- Bacteriology Division, United States Army Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Catherine L Wilhelmsen
- Pathology Division, United States Army of Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Jolynn W Raymond
- Pathology Division, United States Army of Medical Research Institute of Infectious Diseases Fort Detrick, MD, USA
| | - Nela Zavaljevski
- Telemedicine and Advanced Technology Research Center, Biotechnology HPC Software Applications Institute, United States Army Medical Research and Materiel Command Fort Detrick, MD, USA
| | - Jaques Reifman
- Telemedicine and Advanced Technology Research Center, Biotechnology HPC Software Applications Institute, United States Army Medical Research and Materiel Command Fort Detrick, MD, USA
| | - Anders Wallqvist
- Telemedicine and Advanced Technology Research Center, Biotechnology HPC Software Applications Institute, United States Army Medical Research and Materiel Command Fort Detrick, MD, USA
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Sonah H, Deshmukh RK, Bélanger RR. Computational Prediction of Effector Proteins in Fungi: Opportunities and Challenges. FRONTIERS IN PLANT SCIENCE 2016; 7:126. [PMID: 26904083 PMCID: PMC4751359 DOI: 10.3389/fpls.2016.00126] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2015] [Accepted: 01/23/2016] [Indexed: 05/20/2023]
Abstract
Effector proteins are mostly secretory proteins that stimulate plant infection by manipulating the host response. Identifying fungal effector proteins and understanding their function is of great importance in efforts to curb losses to plant diseases. Recent advances in high-throughput sequencing technologies have facilitated the availability of several fungal genomes and 1000s of transcriptomes. As a result, the growing amount of genomic information has provided great opportunities to identify putative effector proteins in different fungal species. There is little consensus over the annotation and functionality of effector proteins, and mostly small secretory proteins are considered as effector proteins, a concept that tends to overestimate the number of proteins involved in a plant-pathogen interaction. With the characterization of Avr genes, criteria for computational prediction of effector proteins are becoming more efficient. There are 100s of tools available for the identification of conserved motifs, signature sequences and structural features in the proteins. Many pipelines and online servers, which combine several tools, are made available to perform genome-wide identification of effector proteins. In this review, available tools and pipelines, their strength and limitations for effective identification of fungal effector proteins are discussed. We also present an exhaustive list of classically secreted proteins along with their key conserved motifs found in 12 common plant pathogens (11 fungi and one oomycete) through an analytical pipeline.
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Affiliation(s)
| | | | - Richard R. Bélanger
- Département de Phytologie, Faculté des Sciences de l’Agriculture et de l’Alimentation, Centre de Recherche en Horticulture, Université Laval, QuébecQC, Canada
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Abstract
Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. The purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.
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Memišević V, Zavaljevski N, Rajagopala SV, Kwon K, Pieper R, DeShazer D, Reifman J, Wallqvist A. Mining host-pathogen protein interactions to characterize Burkholderia mallei infectivity mechanisms. PLoS Comput Biol 2015; 11:e1004088. [PMID: 25738731 PMCID: PMC4349708 DOI: 10.1371/journal.pcbi.1004088] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2014] [Accepted: 12/15/2014] [Indexed: 01/01/2023] Open
Abstract
Burkholderia pathogenicity relies on protein virulence factors to control and promote bacterial internalization, survival, and replication within eukaryotic host cells. We recently used yeast two-hybrid (Y2H) screening to identify a small set of novel Burkholderia proteins that were shown to attenuate disease progression in an aerosol infection animal model using the virulent Burkholderia mallei ATCC 23344 strain. Here, we performed an extended analysis of primarily nine B. mallei virulence factors and their interactions with human proteins to map out how the bacteria can influence and alter host processes and pathways. Specifically, we employed topological analyses to assess the connectivity patterns of targeted host proteins, identify modules of pathogen-interacting host proteins linked to processes promoting infectivity, and evaluate the effect of crosstalk among the identified host protein modules. Overall, our analysis showed that the targeted host proteins generally had a large number of interacting partners and interacted with other host proteins that were also targeted by B. mallei proteins. We also introduced a novel Host-Pathogen Interaction Alignment (HPIA) algorithm and used it to explore similarities between host-pathogen interactions of B. mallei, Yersinia pestis, and Salmonella enterica. We inferred putative roles of B. mallei proteins based on the roles of their aligned Y. pestis and S. enterica partners and showed that up to 73% of the predicted roles matched existing annotations. A key insight into Burkholderia pathogenicity derived from these analyses of Y2H host-pathogen interactions is the identification of eukaryotic-specific targeted cellular mechanisms, including the ubiquitination degradation system and the use of the focal adhesion pathway as a fulcrum for transmitting mechanical forces and regulatory signals. This provides the mechanisms to modulate and adapt the host-cell environment for the successful establishment of host infections and intracellular spread. Burkholderia species need to manipulate many host processes and pathways in order to establish a successful intracellular infection in eukaryotic host organisms. Burkholderia mallei uses secreted virulence factor proteins as a means to execute host-pathogen interactions and promote pathogenesis. While validated virulence factor proteins have been shown to attenuate infection in animal models, their actual roles in modifying and influencing host processes are not well understood. Here, we used host-pathogen protein-protein interactions derived from yeast two-hybrid screens to study nine known B. mallei virulence factors and map out potential virulence mechanisms. From the data, we derived both general and specific insights into Burkholderia host-pathogen infectivity pathways. We showed that B. mallei virulence factors tended to target multifunctional host proteins, proteins that interacted with each other, and host proteins with a large number of interacting partners. We also identified similarities between host-pathogen interactions of B. mallei, Yersinia pestis, and Salmonella enterica using a novel host-pathogen interactions alignment algorithm. Importantly, our data are compatible with a framework in which multiple B. mallei virulence factors broadly influence key host processes related to ubiquitin-mediated proteolysis and focal adhesion. This provides B. mallei the means to modulate and adapt the host-cell environment to advance infection.
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Affiliation(s)
- Vesna Memišević
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Nela Zavaljevski
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | | | - Keehwan Kwon
- J. Craig Venter Institute, Rockville, Maryland, United States of America
| | - Rembert Pieper
- J. Craig Venter Institute, Rockville, Maryland, United States of America
| | - David DeShazer
- Bacteriology Division, U.S. Army Medical Research Institute of Infectious Diseases, Fort Detrick, Maryland, United States of America
| | - Jaques Reifman
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
- * E-mail:
| | - Anders Wallqvist
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
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