1
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Silva AF, Torres MDT, Silva LS, Alves FL, Miranda A, Oliveira VX, de la Fuente-Nunez C, Pinheiro AAS. Synthetic angiotensin II peptide derivatives confer protection against cerebral and severe non-cerebral malaria in murine models. Sci Rep 2024; 14:4682. [PMID: 38409185 PMCID: PMC10897374 DOI: 10.1038/s41598-024-51267-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 01/03/2024] [Indexed: 02/28/2024] Open
Abstract
Malaria can have severe long-term effects. Even after treatment with antimalarial drugs eliminates the parasite, survivors of cerebral malaria may suffer from irreversible brain damage, leading to cognitive deficits. Angiotensin II, a natural human peptide hormone that regulates blood pressure, has been shown to be active against Plasmodium spp., the etiologic agent of malaria. Here, we tested two Ang II derivatives that do not elicit vasoconstriction in mice: VIPF, a linear tetrapeptide, which constitutes part of the hydrophobic portion of Ang II; and Ang II-SS, a disulfide-bridged derivative. The antiplasmodial potential of both peptides was evaluated with two mouse models: an experimental cerebral malaria model and a mouse model of non-cerebral malaria. The latter consisted of BALB/c mice infected with Plasmodium berghei ANKA. The peptides had no effect on mean blood pressure and significantly reduced parasitemia in both mouse models. Both peptides reduced the SHIRPA score, an assay used to assess murine health and behavior. However, only the constrained derivative (Ang II-SS), which was also resistant to proteolytic degradation, significantly increased mouse survival. Here, we show that synthetic peptides derived from Ang II are capable of conferring protection against severe manifestations of malaria in mouse models while overcoming the vasoconstrictive side effects of the parent peptide.
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Affiliation(s)
- Adriana F Silva
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, SP, Brazil
- Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brazil
| | - Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Chemistry, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Leandro S Silva
- Division of Infectious Diseases and Immunology, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Flavio L Alves
- Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brazil
- Faculdade de Ciências Médicas da Santa Casa de São Paulo, São Paulo, SP, Brazil
| | - Antonio Miranda
- Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brazil
| | - Vani X Oliveira
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, SP, Brazil
- Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brazil
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Chemistry, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA, USA.
| | - Ana Acacia S Pinheiro
- Instituto de Biofísica Carlos Chagas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
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2
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de Araujo WR, Lukas H, Torres MDT, Gao W, de la Fuente-Nunez C. Low-Cost Biosensor Technologies for Rapid Detection of COVID-19 and Future Pandemics. ACS Nano 2024; 18:1757-1777. [PMID: 38189684 DOI: 10.1021/acsnano.3c01629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Many systems have been designed for the detection of SARS-CoV-2, which is the virus that causes COVID-19. SARS-CoV-2 is readily transmitted, resulting in the rapid spread of disease in human populations. Frequent testing at the point of care (POC) is a key aspect for controlling outbreaks caused by SARS-CoV-2 and other emerging pathogens, as the early identification of infected individuals can then be followed by appropriate measures of isolation or treatment, maximizing the chances of recovery and preventing infectious spread. Diagnostic tools used for high-frequency testing should be inexpensive, provide a rapid diagnostic response without sophisticated equipment, and be amenable to manufacturing on a large scale. The application of these devices should enable large-scale data collection, help control viral transmission, and prevent disease propagation. Here we review functional nanomaterial-based optical and electrochemical biosensors for accessible POC testing for COVID-19. These biosensors incorporate nanomaterials coupled with paper-based analytical devices and other inexpensive substrates, traditional lateral flow technology (antigen and antibody immunoassays), and innovative biosensing methods. We critically discuss the advantages and disadvantages of nanobiosensor-based approaches compared to widely used technologies such as PCR, ELISA, and LAMP. Moreover, we delineate the main technological, (bio)chemical, translational, and regulatory challenges associated with developing functional and reliable biosensors, which have prevented their translation into the clinic. Finally, we highlight how nanobiosensors, given their unique advantages over existing diagnostic tests, may help in future pandemics.
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Affiliation(s)
- William Reis de Araujo
- Portable Chemical Sensors Lab, Department of Analytical Chemistry, Institute of Chemistry, State University of Campinas - UNICAMP, Campinas, SP 13083-970, Brazil
| | - Heather Lukas
- Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, California 91125, United States
| | - Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Wei Gao
- Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, California 91125, United States
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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3
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Chiloeches A, Zágora J, Plachá D, Torres MDT, de la Fuente-Nunez C, López-Fabal F, Gil-Romero Y, Fernández-García R, Fernández-García M, Echeverría C, Muñoz-Bonilla A. Synergistic Combination of Antimicrobial Peptides and Cationic Polyitaconates in Multifunctional PLA Fibers. ACS Appl Bio Mater 2023; 6:4805-4813. [PMID: 37862451 PMCID: PMC10852355 DOI: 10.1021/acsabm.3c00576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 10/05/2023] [Indexed: 10/22/2023]
Abstract
Combining different antimicrobial agents has emerged as a promising strategy to enhance efficacy and address resistance evolution. In this study, we investigated the synergistic antimicrobial effect of a cationic biobased polymer and the antimicrobial peptide (AMP) temporin L, with the goal of developing multifunctional electrospun fibers for potential biomedical applications, particularly in wound dressing. A clickable polymer with pendent alkyne groups was synthesized by using a biobased itaconic acid building block. Subsequently, the polymer was functionalized through click chemistry with thiazolium groups derived from vitamin B1 (PTTIQ), as well as a combination of thiazolium and AMP temporin L, resulting in a conjugate polymer-peptide (PTTIQ-AMP). The individual and combined effects of the cationic PTTIQ, Temporin L, and PTTIQ-AMP were evaluated against Gram-positive and Gram-negative bacteria as well as Candida species. The results demonstrated that most combinations exhibited an indifferent effect, whereas the covalently conjugated PTTIQ-AMP displayed an antagonistic effect, potentially attributed to the aggregation process. Both antimicrobial compounds, PTTIQ and temporin L, were incorporated into poly(lactic acid) electrospun fibers using the supercritical solvent impregnation method. This approach yielded fibers with improved antibacterial performance, as a result of the potent activity exerted by the AMP and the nonleaching nature of the cationic polymer, thereby enhancing long-term effectiveness.
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Affiliation(s)
- Alberto Chiloeches
- Instituto
de Ciencia y Tecnología de Polímeros (ICTP-CSIC), C/Juan de la Cierva 3, Madrid 28006, Spain
- Universidad
Nacional de Educación a Distancia (UNED), C/Bravo Murillo 38, Madrid 28015, Spain
| | - Jakub Zágora
- Nanotechnology
Centre, CEET, VSB—Technical University
of Ostrava, 17. Listopadu 2172/15, Ostrava-Poruba 708 00, Czech Republic
| | - Daniela Plachá
- Nanotechnology
Centre, CEET, VSB—Technical University
of Ostrava, 17. Listopadu 2172/15, Ostrava-Poruba 708 00, Czech Republic
| | - Marcelo D. T. Torres
- Machine
Biology Group, Departments of Psychiatry and Microbiology, Institute
for Biomedical Informatics, Institute for Translational Medicine and
Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments
of Bioengineering and Chemical and Biomolecular Engineering, School
of Engineering and Applied Science, University
of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute
for Computational Science, University of
Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Cesar de la Fuente-Nunez
- Machine
Biology Group, Departments of Psychiatry and Microbiology, Institute
for Biomedical Informatics, Institute for Translational Medicine and
Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments
of Bioengineering and Chemical and Biomolecular Engineering, School
of Engineering and Applied Science, University
of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute
for Computational Science, University of
Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Fátima López-Fabal
- Hospital
Universitario de Móstoles C/Dr. Luis Montes, s/n, Móstoles 28935, Madrid, Spain
- Facultad
de Ciencias Experimentales, Universidad
Francisco de Vitoria, Carretera Pozuelo a Majadahonda, Km 1.800, Madrid 28223, Spain
| | - Yolanda Gil-Romero
- Hospital
Universitario de Móstoles C/Dr. Luis Montes, s/n, Móstoles 28935, Madrid, Spain
| | | | - Marta Fernández-García
- Instituto
de Ciencia y Tecnología de Polímeros (ICTP-CSIC), C/Juan de la Cierva 3, Madrid 28006, Spain
| | - Coro Echeverría
- Instituto
de Ciencia y Tecnología de Polímeros (ICTP-CSIC), C/Juan de la Cierva 3, Madrid 28006, Spain
| | - Alexandra Muñoz-Bonilla
- Instituto
de Ciencia y Tecnología de Polímeros (ICTP-CSIC), C/Juan de la Cierva 3, Madrid 28006, Spain
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4
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Torres MDT, Brooks E, Cesaro A, Sberro H, Nicolaou C, Bhatt AS, de la Fuente-Nunez C. Human gut metagenomic mining reveals an untapped source of peptide antibiotics. bioRxiv 2023:2023.08.31.555711. [PMID: 37693399 PMCID: PMC10491270 DOI: 10.1101/2023.08.31.555711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Drug-resistant bacteria are outpacing traditional antibiotic discovery efforts. Here, we computationally mined 444,054 families of putative small proteins from 1,773 human gut metagenomes, identifying 323 peptide antibiotics encoded in small open reading frames (smORFs). To test our computational predictions, 78 peptides were synthesized and screened for antimicrobial activity in vitro, with 59% displaying activity against either pathogens or commensals. Since these peptides were unique compared to previously reported antimicrobial peptides, we termed them smORF-encoded peptides (SEPs). SEPs killed bacteria by targeting their membrane, synergized with each other, and modulated gut commensals, indicating that they may play a role in reconfiguring microbiome communities in addition to counteracting pathogens. The lead candidates were anti-infective in both murine skin abscess and deep thigh infection models. Notably, prevotellin-2 from Prevotella copri presented activity comparable to the commonly used antibiotic polymyxin B. We report the discovery of hundreds of peptide sequences in the human gut.
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Affiliation(s)
- Marcelo D. T. Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
| | - Erin Brooks
- Department of Medicine (Hematology; Blood and Marrow Transplantation), Stanford University, Stanford, CA, United States of America
| | - Angela Cesaro
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
| | - Hila Sberro
- Department of Medicine (Hematology; Blood and Marrow Transplantation), Stanford University, Stanford, CA, United States of America
| | - Cosmos Nicolaou
- Department of Medicine (Hematology; Blood and Marrow Transplantation), Stanford University, Stanford, CA, United States of America
| | - Ami S. Bhatt
- Department of Medicine (Hematology; Blood and Marrow Transplantation), Stanford University, Stanford, CA, United States of America
- Department of Genetics, Stanford University, Stanford, CA, United States of America
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States of America
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5
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Maasch JRMA, Torres MDT, Melo MCR, de la Fuente-Nunez C. Molecular de-extinction of ancient antimicrobial peptides enabled by machine learning. Cell Host Microbe 2023; 31:1260-1274.e6. [PMID: 37516110 DOI: 10.1016/j.chom.2023.07.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 05/12/2023] [Accepted: 07/06/2023] [Indexed: 07/31/2023]
Abstract
Molecular de-extinction could offer avenues for drug discovery by reintroducing bioactive molecules that are no longer encoded by extant organisms. To prospect for antimicrobial peptides encrypted within extinct and extant human proteins, we introduce the panCleave random forest model for proteome-wide cleavage site prediction. Our model outperformed multiple protease-specific cleavage site classifiers for three modern human caspases, despite its pan-protease design. Antimicrobial activity was observed in vitro for modern and archaic protein fragments identified with panCleave. Lead peptides showed resistance to proteolysis and exhibited variable membrane permeabilization. Additionally, representative modern and archaic protein fragments showed anti-infective efficacy against A. baumannii in both a skin abscess infection model and a preclinical murine thigh infection model. These results suggest that machine-learning-based encrypted peptide prospection can identify stable, nontoxic peptide antibiotics. Moreover, we establish molecular de-extinction through paleoproteome mining as a framework for antibacterial drug discovery.
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Affiliation(s)
- Jacqueline R M A Maasch
- Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marcelo C R Melo
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA.
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6
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Cesaro A, Bagheri M, Torres MDT, Wan F, de la Fuente-Nunez C. Deep learning tools to accelerate antibiotic discovery. Expert Opin Drug Discov 2023; 18:1245-1257. [PMID: 37794737 PMCID: PMC10790350 DOI: 10.1080/17460441.2023.2250721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 08/18/2023] [Indexed: 10/06/2023]
Abstract
INTRODUCTION As machine learning (ML) and artificial intelligence (AI) expand to many segments of our society, they are increasingly being used for drug discovery. Recent deep learning models offer an efficient way to explore high-dimensional data and design compounds with desired properties, including those with antibacterial activity. AREAS COVERED This review covers key frameworks in antibiotic discovery, highlighting physicochemical features and addressing dataset limitations. The deep learning approaches here described include discriminative models such as convolutional neural networks, recurrent neural networks, graph neural networks, and generative models like neural language models, variational autoencoders, generative adversarial networks, normalizing flow, and diffusion models. As the integration of these approaches in drug discovery continues to evolve, this review aims to provide insights into promising prospects and challenges that lie ahead in harnessing such technologies for the development of antibiotics. EXPERT OPINION Accurate antimicrobial prediction using deep learning faces challenges such as imbalanced data, limited datasets, experimental validation, target strains, and structure. The integration of deep generative models with bioinformatics, molecular dynamics, and data augmentation holds the potential to overcome these challenges, enhance model performance, and utlimately accelerate antimicrobial discovery.
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Affiliation(s)
- Angela Cesaro
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Mojtaba Bagheri
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Marcelo D. T. Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Fangping Wan
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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7
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Ageitos L, Torres MDT, de la Fuente-Nunez C. Biologically Active Peptides from Venoms: Applications in Antibiotic Resistance, Cancer, and Beyond. Int J Mol Sci 2022; 23:ijms232315437. [PMID: 36499761 PMCID: PMC9740984 DOI: 10.3390/ijms232315437] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 10/04/2022] [Accepted: 10/06/2022] [Indexed: 12/12/2022] Open
Abstract
Peptides are potential therapeutic alternatives against global diseases, such as antimicrobial-resistant infections and cancer. Venoms are a rich source of bioactive peptides that have evolved over time to act on specific targets of the prey. Peptides are one of the main components responsible for the biological activity and toxicity of venoms. South American organisms such as scorpions, snakes, and spiders are important producers of a myriad of peptides with different biological activities. In this review, we report the main venom-derived peptide families produced from South American organisms and their corresponding activities and biological targets.
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Affiliation(s)
- Lucía Ageitos
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marcelo D. T. Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Correspondence:
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8
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Arqué X, Torres MDT, Patiño T, Boaro A, Sánchez S, de la Fuente-Nunez C. Autonomous Treatment of Bacterial Infections in Vivo Using Antimicrobial Micro- and Nanomotors. ACS Nano 2022; 16:7547-7558. [PMID: 35486889 PMCID: PMC9134509 DOI: 10.1021/acsnano.1c11013] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
The increasing resistance of bacteria to existing antibiotics constitutes a major public health threat globally. Most current antibiotic treatments are hindered by poor delivery to the infection site, leading to undesired off-target effects and drug resistance development and spread. Here, we describe micro- and nanomotors that effectively and autonomously deliver antibiotic payloads to the target area. The active motion and antimicrobial activity of the silica-based robots are driven by catalysis of the enzyme urease and antimicrobial peptides, respectively. These antimicrobial motors show micromolar bactericidal activity in vitro against different Gram-positive and Gram-negative pathogenic bacterial strains and act by rapidly depolarizing their membrane. Finally, they demonstrated autonomous anti-infective efficacy in vivo in a clinically relevant abscess infection mouse model. In summary, our motors combine navigation, catalytic conversion, and bactericidal capacity to deliver antimicrobial payloads to specific infection sites. This technology represents a much-needed tool to direct therapeutics to their target to help combat drug-resistant infections.
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Affiliation(s)
- Xavier Arqué
- Institute
for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
| | - Marcelo D. T. Torres
- Machine
Biology Group, Departments of Psychiatry and Microbiology, Institute
for Biomedical Informatics, Institute for Translational Medicine and
Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments
of Bioengineering and Chemical and Biomolecular Engineering, School
of Engineering and Applied Science, University
of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn
Institute for Computational Science, University
of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Tania Patiño
- Institute
for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
- Chemistry
Department, University of Rome, Tor Vergata, Rome 00133, Italy
| | - Andreia Boaro
- Machine
Biology Group, Departments of Psychiatry and Microbiology, Institute
for Biomedical Informatics, Institute for Translational Medicine and
Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments
of Bioengineering and Chemical and Biomolecular Engineering, School
of Engineering and Applied Science, University
of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn
Institute for Computational Science, University
of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Samuel Sánchez
- Institute
for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
- Institució
Catalana de Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain
| | - Cesar de la Fuente-Nunez
- Machine
Biology Group, Departments of Psychiatry and Microbiology, Institute
for Biomedical Informatics, Institute for Translational Medicine and
Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments
of Bioengineering and Chemical and Biomolecular Engineering, School
of Engineering and Applied Science, University
of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn
Institute for Computational Science, University
of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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9
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Cesaro A, Torres MDT, Gaglione R, Dell'Olmo E, Di Girolamo R, Bosso A, Pizzo E, Haagsman HP, Veldhuizen EJA, de la Fuente-Nunez C, Arciello A. Synthetic Antibiotic Derived from Sequences Encrypted in a Protein from Human Plasma. ACS Nano 2022; 16:1880-1895. [PMID: 35112568 DOI: 10.1021/acsnano.1c04496] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Encrypted peptides have been recently found in the human proteome and represent a potential class of antibiotics. Here we report three peptides derived from the human apolipoprotein B (residues 887-922) that exhibited potent antimicrobial activity against drug-resistant Klebsiella pneumoniae, Acinetobacter baumannii, and Staphylococci both in vitro and in an animal model. The peptides had excellent cytotoxicity profiles, targeted bacteria by depolarizing and permeabilizing their cytoplasmic membrane, inhibited biofilms, and displayed anti-inflammatory properties. Importantly, the peptides, when used in combination, potentiated the activity of conventional antibiotics against bacteria and did not select for bacterial resistance. To ensure translatability of these molecules, a protease resistant retro-inverso variant of the lead encrypted peptide was synthesized and demonstrated anti-infective activity in a preclinical mouse model. Our results provide a link between human plasma and innate immunity and point to the blood as a source of much-needed antimicrobials.
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Affiliation(s)
- Angela Cesaro
- Department of Chemical Sciences, University of Naples Federico II, Naples I-80126, Italy
- Department of Biomolecular Health Sciences, Division of Infectious Diseases and Immunology, Section Molecular Host Defence, Faculty of Veterinary Medicine, Utrecht University, Utrecht 3584 CL, The Netherlands
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Rosa Gaglione
- Department of Chemical Sciences, University of Naples Federico II, Naples I-80126, Italy
- Istituto Nazionale di Biostrutture e Biosistemi (INBB), Rome 00136, Italy
| | - Eliana Dell'Olmo
- Department of Chemical Sciences, University of Naples Federico II, Naples I-80126, Italy
| | - Rocco Di Girolamo
- Department of Chemical Sciences, University of Naples Federico II, Naples I-80126, Italy
| | - Andrea Bosso
- Department of Biology, University of Naples Federico II, Naples I-80126, Italy
| | - Elio Pizzo
- Department of Biology, University of Naples Federico II, Naples I-80126, Italy
| | - Henk P Haagsman
- Department of Biomolecular Health Sciences, Division of Infectious Diseases and Immunology, Section Molecular Host Defence, Faculty of Veterinary Medicine, Utrecht University, Utrecht 3584 CL, The Netherlands
| | - Edwin J A Veldhuizen
- Department of Biomolecular Health Sciences, Division of Infectious Diseases and Immunology, Section Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht 3584 CL, The Netherlands
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Angela Arciello
- Department of Chemical Sciences, University of Naples Federico II, Naples I-80126, Italy
- Istituto Nazionale di Biostrutture e Biosistemi (INBB), Rome 00136, Italy
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10
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Cardoso MH, Chan LY, Cândido ES, Buccini DF, Rezende SB, Torres MDT, Oshiro KGN, Silva ÍC, Gonçalves S, Lu TK, Santos NC, de la Fuente-Nunez C, Craik DJ, Franco OL. An N-capping asparagine–lysine–proline (NKP) motif contributes to a hybrid flexible/stable multifunctional peptide scaffold. Chem Sci 2022; 13:9410-9424. [PMID: 36093022 PMCID: PMC9383710 DOI: 10.1039/d1sc06998e] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 07/10/2022] [Indexed: 11/21/2022] Open
Abstract
Structural diversity drives multiple biological activities and mechanisms of action in linear peptides. Here we describe an unusual N-capping asparagine-lysine-proline (NKP) motif that confers a hybrid multifunctional scaffold to a computationally designed peptide (PaDBS1R7). PaDBS1R7 has a shorter α-helix segment than other computationally designed peptides of similar sequence but with key residue substitutions. Although this motif acts as an α-helix breaker in PaDBS1R7, the Asn5 presents exclusive N-capping effects, forming a belt to establish hydrogen bonds for an amphipathic α-helix stabilization. The combination of these different structural profiles was described as a coil/N-cap/α-helix scaffold, which was also observed in diverse computational peptide mutants. Biological studies revealed that all peptides displayed antibacterial activities. However, only PaDBS1R7 displayed anticancer properties, eradicated Pseudomonas aeruginosa biofilms, decreased bacterial counts by 100–1000-fold in vivo, reduced lipopolysaccharide-induced macrophages stress, and stimulated fibroblast migration for wound healing. This study extends our understanding of an N-capping NKP motif to engineering hybrid multifunctional peptide drug candidates with potent anti-infective and immunomodulatory properties. An unusual N-capping asparagine-lysine-proline (5NKP7) motif yields a coil/N-cap/α-helix multifunctional scaffold in a computer-made peptide selective for anionic surfaces and with anticancer, antibacterial, antibiofilm, anti-infective (in vivo), and immunomodulatory potential.![]()
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Affiliation(s)
- Marlon H. Cardoso
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco Avenida Tamandaré 6000, Campo Grande – MS, 79117900, Brazil
- Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, SGAN 916 Módulo B, Asa Norte, Brasília – DF, 70790160, Brazil
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília – DF, 70910900, Brazil
- Instituto de Biociências (INBIO), Universidade Federal de Mato Grosso do Sul, Cidade Universitária, 79070900, Campo Grande, Mato Grosso do Sul, Brazil
| | - Lai Y. Chan
- Institute for Molecular Bioscience, Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Elizabete S. Cândido
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco Avenida Tamandaré 6000, Campo Grande – MS, 79117900, Brazil
- Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, SGAN 916 Módulo B, Asa Norte, Brasília – DF, 70790160, Brazil
| | - Danieli F. Buccini
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco Avenida Tamandaré 6000, Campo Grande – MS, 79117900, Brazil
| | - Samilla B. Rezende
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco Avenida Tamandaré 6000, Campo Grande – MS, 79117900, Brazil
| | - Marcelo D. T. Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Karen G. N. Oshiro
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco Avenida Tamandaré 6000, Campo Grande – MS, 79117900, Brazil
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília – DF, 70910900, Brazil
| | - Ítala C. Silva
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | - Sónia Gonçalves
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | - Timothy K. Lu
- Synthetic Biology Group, MIT Synthetic Biology Center, The Center for Microbiome Informatics and Therapeutics, Research Laboratory of Electronics, Department of Biological Engineering, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge – MA, 02139, USA
| | - Nuno C. Santos
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David J. Craik
- Institute for Molecular Bioscience, Australian Research Council Centre of Excellence for Innovations in Peptide and Protein Science, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Octávio L. Franco
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco Avenida Tamandaré 6000, Campo Grande – MS, 79117900, Brazil
- Centro de Análises Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, SGAN 916 Módulo B, Asa Norte, Brasília – DF, 70790160, Brazil
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília – DF, 70910900, Brazil
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11
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Meurer M, O’Neil DA, Lovie E, Simpson L, Torres MDT, de la Fuente-Nunez C, Angeles-Boza AM, Kleinsorgen C, Mercer DK, von Köckritz-Blickwede M. Antimicrobial Susceptibility Testing of Antimicrobial Peptides Requires New and Standardized Testing Structures. ACS Infect Dis 2021; 7:2205-2208. [PMID: 34110786 DOI: 10.1021/acsinfecdis.1c00210] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The need for optimized as well as standardized test systems of novel antimicrobial peptides (AMPs) was discussed by experts in the field at the International Meeting on Antimicrobial Peptides (IMAP) 2017 and the 2019 Gordon Research Conference (GRC) on Antimicrobial Peptides, and a survey related to this topic was circulated to participants to collate opinions. The survey included questions ranging from the relevance of susceptibility testing for understanding the mode of action of AMPs, to the importance of optimization and a degree of standardization of test methods and their clinical relevance. Based on the survey results, suggestions for future improvements in the research field are made.
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Affiliation(s)
- Marita Meurer
- Department of Biochemistry, University of Veterinary Medicine Hannover, Foundation, 30559 Hanover, Germany
- Research Center for Emerging Infections and Zoonoses (RIZ), University of Veterinary Medicine Hannover, Foundation, 30559 Hanover, Germany
| | | | - Emma Lovie
- NovaBiotics Ltd, Aberdeen, AB23 8EW, United Kingdom
| | | | - Marcelo D. T. Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Alfredo M. Angeles-Boza
- Department of Chemistry, University of Connecticut, Storrs, Connecticut 06269-3060, United States
- Institute of Materials Science, University of Connecticut, Storrs, Connecticut 06269-3136, United States
| | - Christin Kleinsorgen
- Center for E-Learning, Didactics and Educational Research (ZELDA), University of Veterinary Medicine Hannover, Foundation, 30559 Hanover, Germany
| | | | - Maren von Köckritz-Blickwede
- Department of Biochemistry, University of Veterinary Medicine Hannover, Foundation, 30559 Hanover, Germany
- Research Center for Emerging Infections and Zoonoses (RIZ), University of Veterinary Medicine Hannover, Foundation, 30559 Hanover, Germany
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12
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de Lima LF, Ferreira AL, Torres MDT, de Araujo WR, de la Fuente-Nunez C. Minute-scale detection of SARS-CoV-2 using a low-cost biosensor composed of pencil graphite electrodes. Proc Natl Acad Sci U S A 2021; 118:e2106724118. [PMID: 34244421 PMCID: PMC8325344 DOI: 10.1073/pnas.2106724118] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
COVID-19 has led to over 3.47 million deaths worldwide and continues to devastate primarily middle- and low-income countries. High-frequency testing has been proposed as a potential solution to prevent outbreaks. However, current tests are not sufficiently low-cost, rapid, or scalable to enable broad COVID-19 testing. Here, we describe LEAD (Low-cost Electrochemical Advanced Diagnostic), a diagnostic test that detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within 6.5 min and costs $1.50 per unit to produce using easily accessible and commercially available materials. LEAD is highly sensitive toward SARS-CoV-2 spike protein (limit of detection = 229 fg⋅mL-1) and displays an excellent performance profile using clinical saliva (100.0% sensitivity, 100.0% specificity, and 100.0% accuracy) and nasopharyngeal/oropharyngeal (88.7% sensitivity, 86.0% specificity, and 87.4% accuracy) samples. No cross-reactivity was detected with other coronavirus or influenza strains. Importantly, LEAD also successfully diagnosed the highly contagious SARS-CoV-2 B.1.1.7 UK variant. The device presents high reproducibility under all conditions tested and preserves its original sensitivity for 5 d when stored at 4 °C in phosphate-buffered saline. Our low-cost and do-it-yourself technology opens new avenues to facilitate high-frequency testing and access to much-needed diagnostic tests in resource-limited settings and low-income communities.
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Affiliation(s)
- Lucas F de Lima
- Machine Biology Group, Departments of Psychiatry and Microbiology, University of Pennsylvania, Philadelphia, PA 19104
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104
- Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104
- Portable Chemical Sensors Lab, Department of Analytical Chemistry, Institute of Chemistry, State University of Campinas, São Paulo 13083-970, Brazil
| | - André L Ferreira
- Machine Biology Group, Departments of Psychiatry and Microbiology, University of Pennsylvania, Philadelphia, PA 19104
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104
- Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104
- Portable Chemical Sensors Lab, Department of Analytical Chemistry, Institute of Chemistry, State University of Campinas, São Paulo 13083-970, Brazil
| | - Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, University of Pennsylvania, Philadelphia, PA 19104
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104
- Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104
| | - William R de Araujo
- Portable Chemical Sensors Lab, Department of Analytical Chemistry, Institute of Chemistry, State University of Campinas, São Paulo 13083-970, Brazil
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, University of Pennsylvania, Philadelphia, PA 19104;
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104
- Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104
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13
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Torres MDT, de Araujo WR, de Lima LF, Ferreira AL, de la Fuente-Nunez C. Low-cost biosensor for rapid detection of SARS-CoV-2 at the point of care. Matter 2021; 4:2403-2416. [PMID: 33997767 PMCID: PMC8106877 DOI: 10.1016/j.matt.2021.05.003] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 04/28/2021] [Accepted: 05/06/2021] [Indexed: 05/20/2023]
Abstract
SARS-CoV-2, the virus that causes COVID-19, has killed over 3 million people worldwide. Despite the urgency of the current pandemic, most available diagnostic methods for COVID-19 use RT-PCR to detect nucleic acid sequences specific to SARS-CoV-2. These tests are limited by their requirement of a large laboratory space, high reagent costs, multistep sample preparation, and the potential for cross-contamination. Moreover, results usually take hours to days to become available. Therefore, fast, reliable, inexpensive, and scalable point-of-care diagnostics are urgently needed. Here, we describe RAPID 1.0, a simple, handheld, and highly sensitive miniaturized biosensor modified with human receptor angiotensin-converting enzyme-2. RAPID 1.0 can detect SARS-CoV-2 using 10 μL of sample within 4 min through its increased resistance to charge transfer of a redox probe measured by electrochemical impedance spectroscopy. The sensitivity and specificity of RAPID for nasopharyngeal/oropharyngeal swab and saliva samples are 85.3% and 100% and 100% and 86.5%, respectively.
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Affiliation(s)
- Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William R de Araujo
- Portable Chemical Sensors Lab, Department of Analytical Chemistry, Institute of Chemistry, State University of Campinas - UNICAMP, Campinas, Sao Paulo 13083-970, Brazil
| | - Lucas F de Lima
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Portable Chemical Sensors Lab, Department of Analytical Chemistry, Institute of Chemistry, State University of Campinas - UNICAMP, Campinas, Sao Paulo 13083-970, Brazil
| | - André L Ferreira
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Portable Chemical Sensors Lab, Department of Analytical Chemistry, Institute of Chemistry, State University of Campinas - UNICAMP, Campinas, Sao Paulo 13083-970, Brazil
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA
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14
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Abstract
Antibiotic resistance is one of the greatest challenges of our time. This global health problem originated from a paucity of truly effective antibiotic classes and an increased incidence of multi-drug-resistant bacterial isolates in hospitals worldwide. Indeed, it has been recently estimated that 10 million people will die annually from drug-resistant infections by the year 2050. Therefore, the need to develop out-of-the-box strategies to combat antibiotic resistance is urgent. The biological world has provided natural templates, called antimicrobial peptides (AMPs), which exhibit multiple intrinsic medical properties including the targeting of bacteria. AMPs can be used as scaffolds and, via engineering, can be reconfigured for optimized potency and targetability toward drug-resistant pathogens. Here, we review the recent development of tools for the discovery, design, and production of AMPs and propose that the future of peptide drug discovery will involve the convergence of computational and synthetic biology principles.
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Affiliation(s)
- Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Jicong Cao
- Synthetic Biology Group, MIT Synthetic Biology Center, Department of Biological Engineering and Electrical Engineering and Computer Science, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Octavio L Franco
- Centro de Análises Proteômicas e Bioquímicas, Universidade Católica de Brasília, Brasília, DF 70790160, Brazil
- S-inova Biotech, Universidade Católica Dom Bosco, Campo Grande, MS 79117010, Brazil
| | - Timothy K Lu
- Synthetic Biology Group, MIT Synthetic Biology Center, Department of Biological Engineering and Electrical Engineering and Computer Science, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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15
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Silveira GGOS, Torres MDT, Ribeiro CFA, Meneguetti BT, Carvalho CME, de la Fuente-Nunez C, Franco OL, Cardoso MH. Antibiofilm Peptides: Relevant Preclinical Animal Infection Models and Translational Potential. ACS Pharmacol Transl Sci 2021; 4:55-73. [PMID: 33615161 DOI: 10.1021/acsptsci.0c00191] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Indexed: 12/21/2022]
Abstract
Biofilm-forming bacteria may be 10-1000 times more resistant to antibiotics than planktonic bacteria and represent about 75% of bacterial infections in humans. Antibiofilm treatments are scarce, and no effective therapies have been reported so far. In this context, antibiofilm peptides (ABPs) represent an exciting class of agents with potent activity against biofilms both in vitro and in vivo. Moreover, murine models of bacterial biofilm infections have been used to evaluate the in vivo effectiveness of ABPs. Therefore, here we highlight the translational potential of ABPs and provide an overview of the different clinically relevant murine models to assess ABP efficacy, including wound, foreign body, chronic lung, and oral models of infection. We discuss key challenges to translate ABPs to the clinic and the pros and cons of the existing murine biofilm models for reliable assessment of the efficacy of ABPs.
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Affiliation(s)
- Gislaine G O S Silveira
- S-Inova Biotech, Programa de Pós-Graduação Stricto Sensu em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, Mato Grosso do Sul 79117-010, Brazil
| | - Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.,Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.,Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Camila F A Ribeiro
- S-Inova Biotech, Programa de Pós-Graduação Stricto Sensu em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, Mato Grosso do Sul 79117-010, Brazil
| | - Beatriz T Meneguetti
- S-Inova Biotech, Programa de Pós-Graduação Stricto Sensu em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, Mato Grosso do Sul 79117-010, Brazil
| | - Cristiano M E Carvalho
- S-Inova Biotech, Programa de Pós-Graduação Stricto Sensu em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, Mato Grosso do Sul 79117-010, Brazil
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.,Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.,Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Octávio L Franco
- S-Inova Biotech, Programa de Pós-Graduação Stricto Sensu em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, Mato Grosso do Sul 79117-010, Brazil.,Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, Distrito Federal 71966-700, Brazil
| | - Marlon H Cardoso
- S-Inova Biotech, Programa de Pós-Graduação Stricto Sensu em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, Mato Grosso do Sul 79117-010, Brazil.,Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, Distrito Federal 71966-700, Brazil
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16
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Torres MDT, Voskian S, Brown P, Liu A, Lu TK, Hatton TA, de la Fuente-Nunez C. Coatable and Resistance-Proof Ionic Liquid for Pathogen Eradication. ACS Nano 2021; 15:966-978. [PMID: 33438392 DOI: 10.1021/acsnano.0c07642] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Antibiotic-resistant bacteria infect close to 3 million people, and kill 35,000, each year in the United States. Ionic liquid (IL)-based antimicrobial agents have the potential to diversify our ever-diminishing antibiotic arsenal. Here, we describe an IL with potent submicromolar antimicrobial activity in vitro against clinically relevant Gram-negative and Gram-positive bacterial pathogens as well as anti-infective activity in a mouse model. The IL kills pathogenic bacteria such as Acinetobacter baumannii, Salmonella enterica, and Escherichia coli by disrupting their outer membrane and does not select for bacterial resistance. We show incorporation of our IL into surface coatings to generate a type of antibiofilm material. The IL-loaded ionogel surfaces demonstrate high-antimicrobial and antifouling activity by killing bacteria in both static and dynamic tests. Our IL-based antibiofilm surfaces are low-cost and easy to manufacture, can be formed on glass, latex, plastic, and metal surfaces, such as catheters and other medical devices where high local concentrations of antimicrobials are needed, and may have applications in other clinical and industrial settings.
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Affiliation(s)
- Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Sahag Voskian
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Paul Brown
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Andong Liu
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Boston Children's Hospital, Boston, Massachusetts 02115, United States
| | - Timothy K Lu
- Synthetic Biology Group, MIT Synthetic Biology Center, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02139, United States
| | - T Alan Hatton
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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17
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Torres MDT, Silva AF, Andrade GP, Pedron CN, Cerchiaro G, Ribeiro AO, Oliveira VX, de la Fuente‐Nunez C. The wasp venom antimicrobial peptide polybia-CP and its synthetic derivatives display antiplasmodial and anticancer properties. Bioeng Transl Med 2020; 5:e10167. [PMID: 33005737 PMCID: PMC7510464 DOI: 10.1002/btm2.10167] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 05/10/2020] [Accepted: 05/11/2020] [Indexed: 12/11/2022] Open
Abstract
The wasp venom-derived antimicrobial peptide polybia-CP has been previously shown to exhibit potent antimicrobial activity, but it is also highly toxic. Previously, using a physicochemical-guided peptide design strategy, we reversed its toxicity while preserving and even enhancing its antibacterial properties. Here, we report on several additional unanticipated biological properties of polybia-CP and derivatives, namely their ability to target Plasmodium sporozoites and cancer cells. We leverage a physicochemical-guided approach to identify features that operate as functional hotspots making these peptides viable antiplasmodial and anticancer agents. Helical content and net positive charge are identified as key structural and physicochemical determinants for antiplasmodial activity. In addition to helicity and net charge, hydrophobicity-related properties of polybia-CP and derivatives were found to be equally critical to target cancer cells. We demonstrate that by tuning these physicochemical parameters, it is possible to design synthetic peptides with enhanced submicromolar antiplasmodial potency and micromolar anticancer activity. This study reveals novel and previously undescribed functions for Polybia-CP and analogs. Additionally, we demonstrate that a physicochemical-guided rational design strategy can be used for identifying functional hotspots in peptide molecules and for tuning structure-function to generate novel and potent new-to-nature therapies.
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Affiliation(s)
- Marcelo D. T. Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, Penn Institute for Computational Science, and Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Adriana F. Silva
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABCSanto AndréSPBrazil
- Departamento de BioquímicaUniversidade Federal de São PauloSão PauloSPBrazil
| | - Gislaine P. Andrade
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABCSanto AndréSPBrazil
| | - Cibele N. Pedron
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABCSanto AndréSPBrazil
| | - Giselle Cerchiaro
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABCSanto AndréSPBrazil
| | - Anderson O. Ribeiro
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABCSanto AndréSPBrazil
| | - Vani X. Oliveira
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABCSanto AndréSPBrazil
- Departamento de BiofísicaUniversidade Federal de São PauloSão PauloSPBrazil
| | - Cesar de la Fuente‐Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, Penn Institute for Computational Science, and Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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18
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Mercer DK, Torres MDT, Duay SS, Lovie E, Simpson L, von Köckritz-Blickwede M, de la Fuente-Nunez C, O'Neil DA, Angeles-Boza AM. Antimicrobial Susceptibility Testing of Antimicrobial Peptides to Better Predict Efficacy. Front Cell Infect Microbiol 2020; 10:326. [PMID: 32733816 PMCID: PMC7358464 DOI: 10.3389/fcimb.2020.00326] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 05/29/2020] [Indexed: 12/11/2022] Open
Abstract
During the development of antimicrobial peptides (AMP) as potential therapeutics, antimicrobial susceptibility testing (AST) stands as an essential part of the process in identification and optimisation of candidate AMP. Standard methods for AST, developed almost 60 years ago for testing conventional antibiotics, are not necessarily fit for purpose when it comes to determining the susceptibility of microorganisms to AMP. Without careful consideration of the parameters comprising AST there is a risk of failing to identify novel antimicrobials at a time when antimicrobial resistance (AMR) is leading the planet toward a post-antibiotic era. More physiologically/clinically relevant AST will allow better determination of the preclinical activity of drug candidates and allow the identification of lead compounds. An important consideration is the efficacy of AMP in biological matrices replicating sites of infection, e.g., blood/plasma/serum, lung bronchiolar lavage fluid/sputum, urine, biofilms, etc., as this will likely be more predictive of clinical efficacy. Additionally, specific AST for different target microorganisms may help to better predict efficacy of AMP in specific infections. In this manuscript, we describe what we believe are the key considerations for AST of AMP and hope that this information can better guide the preclinical development of AMP toward becoming a new generation of urgently needed antimicrobials.
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Affiliation(s)
| | - Marcelo D. T. Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, Penn Institute for Computational Science, and Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
| | - Searle S. Duay
- Department of Chemistry, Institute of Materials Science, University of Connecticut, Storrs, CT, United States
| | - Emma Lovie
- NovaBiotics Ltd, Aberdeen, United Kingdom
| | | | | | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, Penn Institute for Computational Science, and Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
| | | | - Alfredo M. Angeles-Boza
- Department of Chemistry, Institute of Materials Science, University of Connecticut, Storrs, CT, United States
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19
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Agbale CM, Sarfo JK, Galyuon IK, Juliano SA, Silva GGO, Buccini DF, Cardoso MH, Torres MDT, Angeles-Boza AM, de la Fuente-Nunez C, Franco OL. Antimicrobial and Antibiofilm Activities of Helical Antimicrobial Peptide Sequences Incorporating Metal-Binding Motifs. Biochemistry 2019; 58:3802-3812. [PMID: 31448597 DOI: 10.1021/acs.biochem.9b00440] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Antimicrobial peptides (AMPs) represent alternative strategies to combat the global health problem of antibiotic resistance. However, naturally occurring AMPs are generally not sufficiently active for use as antibiotics. Optimized synthetic versions incorporating additional design principles are needed. Here, we engineered amino-terminal Cu(II) and Ni(II) (ATCUN) binding motifs, which can enhance biological function, into the native sequence of two AMPs, CM15 and citropin1.1. The incorporation of metal-binding motifs modulated the antimicrobial activity of synthetic peptides against a panel of carbapenem-resistant enterococci (CRE) bacteria, including carbapenem-resistant Klebsiella pneumoniae (KpC+) and Escherichia coli (KpC+). Activity modulation depended on the type of ATCUN variant utilized. Membrane permeability assays revealed that the in silico selected lead template, CM15, and its ATCUN analogs increased bacterial cell death. Mass spectrometry, circular dichroism, and molecular dynamics simulations indicated that coordinating ATCUN derivatives with Cu(II) ions did not increase the helical tendencies of the AMPs. CM15 ATCUN variants, when combined with Meropenem, streptomycin, or chloramphenicol, showed synergistic effects against E. coli (KpC+ 1812446) biofilms. Motif addition also reduced the hemolytic activity of the wild-type AMP and improved the survival rate of mice in a systemic infection model. The dependence of these bioactivities on the particular amino acids of the ATCUN motif highlights the possible use of size, charge, and hydrophobicity to fine-tune AMP biological function. Our data indicate that incorporating metal-binding motifs into peptide sequences leads to synthetic variants with modified biological properties. These principles may be applied to augment the activities of other peptide sequences.
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Affiliation(s)
- Caleb M Agbale
- S-INOVA Biotech, Programa de Pós-Graduação em Biotecnologia , Universidade Católica Dom Bosco , Campo Grande , Mato Grosso Do Sul, MS 79117-900 , Brazil.,Department of Biochemistry, School of Biological Sciences, College of Agriculture and Natural Sciences , University of Cape Coast , Cape Coast , Ghana.,Department of Molecular Biology and Biotechnology, School of Biological Sciences, College of Agriculture and Natural Sciences , University of Cape Coast , Cape Coast , Ghana
| | - Justice K Sarfo
- S-INOVA Biotech, Programa de Pós-Graduação em Biotecnologia , Universidade Católica Dom Bosco , Campo Grande , Mato Grosso Do Sul, MS 79117-900 , Brazil
| | - Isaac K Galyuon
- Department of Molecular Biology and Biotechnology, School of Biological Sciences, College of Agriculture and Natural Sciences , University of Cape Coast , Cape Coast , Ghana
| | - Samuel A Juliano
- Department of Chemistry , University of Connecticut , Storrs , Connecticut 06269 , United States
| | - Gislaine G O Silva
- S-INOVA Biotech, Programa de Pós-Graduação em Biotecnologia , Universidade Católica Dom Bosco , Campo Grande , Mato Grosso Do Sul, MS 79117-900 , Brazil
| | - Danieli F Buccini
- S-INOVA Biotech, Programa de Pós-Graduação em Biotecnologia , Universidade Católica Dom Bosco , Campo Grande , Mato Grosso Do Sul, MS 79117-900 , Brazil
| | - Marlon H Cardoso
- S-INOVA Biotech, Programa de Pós-Graduação em Biotecnologia , Universidade Católica Dom Bosco , Campo Grande , Mato Grosso Do Sul, MS 79117-900 , Brazil.,Centro de Análises de Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia , Universidade Católica de Brasília , Brasília , DF 70790-160 , Brazil.,Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina , Universidade de Brasília , Brasília , DF 70910-900 , Brazil
| | - Marcelo D T Torres
- Machine Biology Group, Departments of Psychiatry and Microbiology, Perelman School of Medicine, and Department of Bioengineering , University of Pennsylvania , Philadelphia , Pennsylvania 19104 , United States
| | - Alfredo M Angeles-Boza
- Department of Chemistry , University of Connecticut , Storrs , Connecticut 06269 , United States.,Institute of Materials Science , University of Connecticut , Storrs , Connecticut 06269 , United States
| | - Cesar de la Fuente-Nunez
- Machine Biology Group, Departments of Psychiatry and Microbiology, Perelman School of Medicine, and Department of Bioengineering , University of Pennsylvania , Philadelphia , Pennsylvania 19104 , United States
| | - Octavio L Franco
- S-INOVA Biotech, Programa de Pós-Graduação em Biotecnologia , Universidade Católica Dom Bosco , Campo Grande , Mato Grosso Do Sul, MS 79117-900 , Brazil.,Centro de Análises de Proteômicas e Bioquímicas, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia , Universidade Católica de Brasília , Brasília , DF 70790-160 , Brazil.,Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina , Universidade de Brasília , Brasília , DF 70910-900 , Brazil
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20
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Oshiro KGN, Cândido ES, Chan LY, Torres MDT, Monges BED, Rodrigues SG, Porto WF, Ribeiro SM, Henriques ST, Lu TK, de la Fuente-Nunez C, Craik DJ, Franco OL, Cardoso MH. Computer-Aided Design of Mastoparan-like Peptides Enables the Generation of Nontoxic Variants with Extended Antibacterial Properties. J Med Chem 2019; 62:8140-8151. [DOI: 10.1021/acs.jmedchem.9b00915] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Karen G. N. Oshiro
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Brasília 70910900, Brazil
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande 79117900, Brazil
| | - Elizabete S. Cândido
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande 79117900, Brazil
- Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília 70790160, Brazil
| | - Lai Y. Chan
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Marcelo D. T. Torres
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02139, United States
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, SP, 09210170, Brazil
| | - Bruna E. D. Monges
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande 79117900, Brazil
| | - Silvia G. Rodrigues
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande 79117900, Brazil
| | - William F. Porto
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande 79117900, Brazil
- Porto Reports, Brasília, DF 70790160, Brazil
| | - Suzana M. Ribeiro
- Programa de Pós-Graduação em Ciências da Saúde, Universidade Federal da Grande Dourados, Dourados, MS 79825070, Brazil
| | - Sónia T. Henriques
- Faculty of Health, School of Biomedical Sciences, Institute of Health & Biomedical Innovation, Queensland University of Technology, Translational Research Institute, Brisbane, QLD 4102, Australia
| | - Timothy K. Lu
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02139, United States
| | - Cesar de la Fuente-Nunez
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02139, United States
| | - David J. Craik
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Octávio L. Franco
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Brasília 70910900, Brazil
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande 79117900, Brazil
- Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília 70790160, Brazil
| | - Marlon H. Cardoso
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Brasília 70910900, Brazil
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande 79117900, Brazil
- Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília 70790160, Brazil
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
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21
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Cândido ES, Cardoso MH, Chan LY, Torres MDT, Oshiro KGN, Porto WF, Ribeiro SM, Haney EF, Hancock REW, Lu TK, de la Fuente-Nunez C, Craik DJ, Franco OL. Short Cationic Peptide Derived from Archaea with Dual Antibacterial Properties and Anti-Infective Potential. ACS Infect Dis 2019; 5:1081-1086. [PMID: 31016969 DOI: 10.1021/acsinfecdis.9b00073] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Bacterial biofilms and associated infections represent one of the biggest challenges in the clinic, and as an alternative to counter bacterial infections, antimicrobial peptides have attracted great attention in the past decade. Here, ten short cationic antimicrobial peptides were generated through a sliding-window strategy on the basis of the 19-amino acid residue peptide, derived from a Pyrobaculum aerophilum ribosomal protein. PaDBS1R6F10 exhibited anti-infective potential as it decreased the bacterial burden in murine Pseudomonas aeruginosa cutaneous infections by more than 1000-fold. Adverse cytotoxic and hemolytic effects were not detected against mammalian cells. The peptide demonstrated structural plasticity in terms of its secondary structure in the different environments tested. PaDBS1R6F10 represents a promising antimicrobial agent against bacteria infections, without harming human cells.
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Affiliation(s)
- Elizabete S. Cândido
- Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, SGAN 916 Módulo B, Asa Norte, Brasília, Distrito Federal 70790160, Brazil
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Avenida Tamandaré 6000, Campo Grande, Mato Grosso do Sul 79117900, Brazil
| | - Marlon H. Cardoso
- Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, SGAN 916 Módulo B, Asa Norte, Brasília, Distrito Federal 70790160, Brazil
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Avenida Tamandaré 6000, Campo Grande, Mato Grosso do Sul 79117900, Brazil
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília, Distrito Federal 70910900, Brazil
- Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland 4072, Australia
| | - Lai Y. Chan
- Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland 4072, Australia
| | - Marcelo D. T. Torres
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02139, United States of America
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, São Paulo 09210170, Brazil
| | - Karen G. N. Oshiro
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Avenida Tamandaré 6000, Campo Grande, Mato Grosso do Sul 79117900, Brazil
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília, Distrito Federal 70910900, Brazil
| | - William F. Porto
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Avenida Tamandaré 6000, Campo Grande, Mato Grosso do Sul 79117900, Brazil
- Porto Reports, Brasília, Distrito Federal 70790160, Brazil
| | - Suzana M. Ribeiro
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Avenida Tamandaré 6000, Campo Grande, Mato Grosso do Sul 79117900, Brazil
| | - Evan F. Haney
- Centre for Microbial Diseases and Immunity Research, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Robert E. W. Hancock
- Centre for Microbial Diseases and Immunity Research, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Timothy K. Lu
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02139, United States of America
| | - Cesar de la Fuente-Nunez
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02139, United States of America
| | - David J. Craik
- Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland 4072, Australia
| | - Octávio L. Franco
- Centro de Análises Proteômicas e Bioquímicas, Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, SGAN 916 Módulo B, Asa Norte, Brasília, Distrito Federal 70790160, Brazil
- S-Inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Avenida Tamandaré 6000, Campo Grande, Mato Grosso do Sul 79117900, Brazil
- Programa de Pós-Graduação em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília, Distrito Federal 70910900, Brazil
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22
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Torres MDT, Pedron CN, Higashikuni Y, Kramer RM, Cardoso MH, Oshiro KGN, Franco OL, Silva Junior PI, Silva FD, Oliveira Junior VX, Lu TK, de la Fuente-Nunez C. Structure-function-guided exploration of the antimicrobial peptide polybia-CP identifies activity determinants and generates synthetic therapeutic candidates. Commun Biol 2018; 1:221. [PMID: 30534613 PMCID: PMC6286318 DOI: 10.1038/s42003-018-0224-2] [Citation(s) in RCA: 100] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Accepted: 10/18/2018] [Indexed: 12/20/2022] Open
Abstract
Antimicrobial peptides (AMPs) constitute promising alternatives to classical antibiotics for the treatment of drug-resistant infections, which are a rapidly emerging global health challenge. However, our understanding of the structure-function relationships of AMPs is limited, and we are just beginning to rationally engineer peptides in order to develop them as therapeutics. Here, we leverage a physicochemical-guided peptide design strategy to identify specific functional hotspots in the wasp-derived AMP polybia-CP and turn this toxic peptide into a viable antimicrobial. Helical fraction, hydrophobicity, and hydrophobic moment are identified as key structural and physicochemical determinants of antimicrobial activity, utilized in combination with rational engineering to generate synthetic AMPs with therapeutic activity in a mouse model. We demonstrate that, by tuning these physicochemical parameters, it is possible to design nontoxic synthetic peptides with enhanced sub-micromolar antimicrobial potency in vitro and anti-infective activity in vivo. We present a physicochemical-guided rational design strategy to generate peptide antibiotics.
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Affiliation(s)
- Marcelo D. T. Torres
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, SP 09210580 Brazil
| | - Cibele N. Pedron
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, SP 09210580 Brazil
| | - Yasutomi Higashikuni
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA
| | - Robin M. Kramer
- Division of Comparative Medicine, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Marlon H. Cardoso
- Programa de Pós-Gradução em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Brasília, DF 70297400 Brazil
- Centro de Análises Proteômicas e Bioquímicas, Universidade Católica de Brasília, Brasília, DF 71966700 Brazil
- S-inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, MS 79117010 Brazil
| | - Karen G. N. Oshiro
- S-inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, MS 79117010 Brazil
| | - Octávio L. Franco
- Programa de Pós-Gradução em Patologia Molecular, Faculdade de Medicina, Universidade de Brasília, Brasília, DF 70297400 Brazil
- Centro de Análises Proteômicas e Bioquímicas, Universidade Católica de Brasília, Brasília, DF 71966700 Brazil
- S-inova Biotech, Programa de Pós-Graduação em Biotecnologia, Universidade Católica Dom Bosco, Campo Grande, MS 79117010 Brazil
| | - Pedro I. Silva Junior
- Laboratório Especial de Toxinologia Aplicada, Instituto Butantan, São Paulo, SP 05503900 Brazil
| | - Fernanda D. Silva
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, SP 09210580 Brazil
| | - Vani X. Oliveira Junior
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, SP 09210580 Brazil
| | - Timothy K. Lu
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA
| | - Cesar de la Fuente-Nunez
- Synthetic Biology Group, MIT Synthetic Biology Center; The Center for Microbiome Informatics and Therapeutics; Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA
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23
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Torres MDT, Andrade GP, Sato RH, Pedron CN, Manieri TM, Cerchiaro G, Ribeiro AO, de la Fuente-Nunez C, Oliveira VX. Natural and redesigned wasp venom peptides with selective antitumoral activity. Beilstein J Org Chem 2018; 14:1693-1703. [PMID: 30013694 PMCID: PMC6036970 DOI: 10.3762/bjoc.14.144] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Accepted: 06/13/2018] [Indexed: 12/16/2022] Open
Abstract
About 1 in 8 U.S. women (≈12%) will develop invasive breast cancer over the course of their lifetime. Surgery, chemotherapy, radiotherapy, and hormone manipulation constitute the major treatment options for breast cancer. Here, we show that both a natural antimicrobial peptide (AMP) derived from wasp venom (decoralin, Dec-NH2), and its synthetic variants generated via peptide design, display potent activity against cancer cells. We tested the derivatives at increasing doses and observed anticancer activity at concentrations as low as 12.5 μmol L−1 for the selective targeting of MCF-7 breast cancer cells. Flow cytometry assays further revealed that treatment with wild-type (WT) peptide Dec-NH2 led to necrosis of MCF-7 cells. Additional atomic force microscopy (AFM) measurements indicated that the roughness of cancer cell membranes increased significantly when treated with lead peptides compared to controls. Biophysical features such as helicity, hydrophobicity, and net positive charge were identified to play an important role in the anticancer activity of the peptides. Indeed, abrupt changes in peptide hydrophobicity and conformational propensity led to peptide inactivation, whereas increasing the net positive charge of peptides enhanced their activity. We present peptide templates with selective activity towards breast cancer cells that leave normal cells unaffected. These templates represent excellent scaffolds for the design of selective anticancer peptide therapeutics.
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Affiliation(s)
- Marcelo D T Torres
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, 09210580, SP, Brazil.,Synthetic Biology Group, MIT Synthetic Biology Center, Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology; Broad Institute of MIT and Harvard, The Center for Microbiome Informatics and Therapeutics, Cambridge, 02139, MA, United States of America
| | - Gislaine P Andrade
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, 09210580, SP, Brazil
| | - Roseli H Sato
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, 09210580, SP, Brazil
| | - Cibele N Pedron
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, 09210580, SP, Brazil
| | - Tania M Manieri
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, 09210580, SP, Brazil
| | - Giselle Cerchiaro
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, 09210580, SP, Brazil
| | - Anderson O Ribeiro
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, 09210580, SP, Brazil
| | - Cesar de la Fuente-Nunez
- Synthetic Biology Group, MIT Synthetic Biology Center, Research Laboratory of Electronics, Department of Biological Engineering, and Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology; Broad Institute of MIT and Harvard, The Center for Microbiome Informatics and Therapeutics, Cambridge, 02139, MA, United States of America
| | - Vani X Oliveira
- Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, Santo André, 09210580, SP, Brazil
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24
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Torres MDT, Silva AF, Pedron CN, Capurro ML, de la Fuente‐Nunez C, Junior VXO. Peptide Design Enables Reengineering of an Inactive Wasp Venom Peptide into Synthetic Antiplasmodial Agents. ChemistrySelect 2018. [DOI: 10.1002/slct.201800529] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Marcelo D. T. Torres
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABC
- Synthetic Biology Group
- Research Laboratory of Electronics
- Department of Biological Engineering and Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyCambridge, MassachusettsUnited States of America
- Broad Institute of MIT and Harvard, Cambridge, MassachusettsUnited States of America
| | - Adriana F. Silva
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABC
| | - Cibele N. Pedron
- Centro de Ciências Naturais e HumanasUniversidade Federal do ABC
| | | | - Cesar de la Fuente‐Nunez
- Synthetic Biology Group
- Research Laboratory of Electronics
- Department of Biological Engineering and Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyCambridge, MassachusettsUnited States of America
- Broad Institute of MIT and Harvard, Cambridge, MassachusettsUnited States of America
- The Center for Microbiome Informatics and Therapeutics, Cambridge, Massachusetts, United States of America
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25
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Abstract
Polynitroxide films – the first example of surface tethered nitroxides reducing biofilm fouling.
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Affiliation(s)
- Nathan R. B. Boase
- School of Chemistry
- Physics and Mechanical Engineering
- Queensland University of Technology (QUT)
- Brisbane
- Australia
| | - Marcelo D. T. Torres
- Synthetic Biology Group
- MIT Synthetic Biology Center
- Department of Biological Engineering and Electrical Engineering & Computer Science
- Research Laboratory of Electronics
- Massachusetts Institute of Technology
| | - Nicholas L. Fletcher
- Centre for Advanced Imaging
- University of Queensland
- St Lucia
- Australia
- Australian Institute for Bioengineering and Nanotechnology
| | - Cesar de la Fuente-Nunez
- Synthetic Biology Group
- MIT Synthetic Biology Center
- Department of Biological Engineering and Electrical Engineering & Computer Science
- Research Laboratory of Electronics
- Massachusetts Institute of Technology
| | - Kathryn E. Fairfull-Smith
- School of Chemistry
- Physics and Mechanical Engineering
- Queensland University of Technology (QUT)
- Brisbane
- Australia
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26
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Torres MDT, Pedron CN, Araújo I, Silva PI, Silva FD, Oliveira VX. Decoralin Analogs with Increased Resistance to Degradation and Lower Hemolytic Activity. ChemistrySelect 2017. [DOI: 10.1002/slct.201601590] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Marcelo D. T. Torres
- Centro de Ciências Naturais e Humanas; Universidade Federal do ABC; Avenida dos Estados, 5001, 09210580 Santo André Brazil
| | - Cibele N. Pedron
- Centro de Ciências Naturais e Humanas; Universidade Federal do ABC; Avenida dos Estados, 5001, 09210580 Santo André Brazil
| | - Iris Araújo
- Centro de Ciências Naturais e Humanas; Universidade Federal do ABC; Avenida dos Estados, 5001, 09210580 Santo André Brazil
| | - Pedro I. Silva
- Laboratório Especial de Toxinologia Aplicada; Instituto Butantan; Avenida Vital Brasil, 1500, 05503900 São Paulo Brazil
| | - Fernanda D. Silva
- Centro de Ciências Naturais e Humanas; Universidade Federal do ABC; Avenida dos Estados, 5001, 09210580 Santo André Brazil
| | - Vani X. Oliveira
- Centro de Ciências Naturais e Humanas; Universidade Federal do ABC; Avenida dos Estados, 5001, 09210580 Santo André Brazil
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