Paula Alexandra Silva Jorge

New trends in peptide-based anti-biofilm strategies: a review of recent achievements and bioinformatic approaches

Antimicrobial peptides (AMPs) have a broad spectrum of activity and unspecific mechanisms of action. Therefore, they are seen as valid alternatives to overcome clinically relevant biofilms and reduce the chance of acquired resistance. This paper reviews AMPs and anti-biofilm AMP-based strategies and discusses ongoing and future work. Recent studies report successful AMP-based prophylactic and therapeutic strategies, several databases catalogue AMP information and analysis tools, and novel bioinformatics tools are supporting AMP discovery and design. However, most AMP studies are performed with planktonic cultures, and most studies on sessile cells test AMPs on growing rather than mature biofilms. Promising preliminary synergistic studies have to be consubstantiated and the study of functionalized coatings with AMPs must be further explored. Standardized operating protocols, to enforce the repeatability and reproducibility of AMP anti-biofilm tests, and automated means of screening and processing the ever-expanding literature are still missing.

Quorum sensing inhibition in Pseudomonas aeruginosa biofilms: new insights through network mining

Abstract Quorum sensing plays a pivotal role in Pseudomonas aeruginosa’s virulence. This paper reviews experimental results on antimicrobial strategies based on quorum sensing inhibition and discusses current targets in the regulatory network that determines P. aeruginosa biofilm formation and virulence. A bioinformatics framework combining literature mining with information from biomedical ontologies and curated databases was used to create a knowledge network of potential anti-quorum sensing agents for P. aeruginosa. A total of 110 scientific articles, corresponding to 1,004 annotations, were so far included in the network and are analysed in this work. Information on the most studied agents, QS targets and methods is detailed. This knowledge network offers a unique view of existing strategies for quorum sensing inhibition and their main regulatory targets and may be used to readily access otherwise scattered information and to help generate new testable hypotheses. This knowledge network is publicly available at http://pcquorum.org/.

Searching for new strategies against biofilm infections: Colistin-AMP combinations against Pseudomonas aeruginosa and Staphylococcus aureus single- and double-species biofilms

Antimicrobial research is being pressured to look for more effective therapeutics for the ever-growing antibiotic-resistant infections, and antimicrobial peptides (AMP) and antimicrobial combinations are promising solutions. This work evaluates colistin-AMP combinations against two major pathogens, Pseudomonas aeruginosa and Staphylococcus aureus, encompassing non- and resistant strains. Colistin (CST) combined with the AMP temporin A (TEMP-A), citropin 1.1 (CIT-1.1) and tachyplesin I linear analogue (TP-I-L) was tested against planktonic, single- and double-species biofilm cultures. Overall synergy for planktonic P. aeruginosa and synergy/additiveness for planktonic S. aureus were observed. Biofilm growth prevention was achieved with synergy and additiveness. Pre-established 24 h-old biofilms were harder to eradicate, especially for S. aureus and double-species biofilms; still, some synergy and addictiveness was observed for higher concentrations, including for the biofilms of resistant strains. Different treatment times and growth media did not greatly influence AMP activity. CST revealed low toxicity compared with the other AMP but its combinations were toxic for high concentrations. Overall, combinations reduced effective AMP concentrations, mainly in prevention scenarios. Improvement of effectiveness and toxicity of therapeutic strategies will be further investigated.

Construction of antimicrobial peptide-drug combination networks from scientific literature based on a semi-automated curation workflow

Considerable research efforts are being invested in the development of novel antimicrobial therapies effective against the growing number of multi-drug resistant pathogens. Notably, the combination of different agents is increasingly explored as means to exploit and improve individual agent actions while minimizing microorganism resistance. Although there are several databases on antimicrobial agents, scientific literature is the primary source of information on experimental antimicrobial combination testing. This work presents a semi-automated database curation workflow that supports the mining of scientific literature and enables the reconstruction of recently documented antimicrobial combinations. Currently, the database contains data on antimicrobial combinations that have been experimentally tested against Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Listeria monocytogenes and Candida albicans, which are prominent pathogenic organisms and are well-known for their wide and growing resistance to conventional antimicrobials. Researchers are able to explore the experimental results for a single organism or across organisms. Likewise, researchers may look into indirect network associations and identify new potential combinations to be tested. The database is available without charges. Database URL: http://sing.ei.uvigo.es/antimicrobialCombination/

Networking the Way towards Antimicrobial Combination Therapies

The exploration of new antimicrobial combinations is a pressing concern for Clinical Microbiology due to the growing number of resistant strains emerging in healthcare settings and in the general community. Researchers are screening agents with alternative modes of action and interest is rising for the potential of antimicrobial peptides (AMPs). This work presents the first ever network reconstruction of AMP combinations reported in the literature fighting Pseudomonas aeruginosa infections. The network, containing 193 combinations of AMPs with 39 AMPs and 154 traditional antibiotics, is expected to help in the design of new studies, notably by unveiling different mechanisms of action and helping in the prediction of new combinations and synergisms. The challenges faced in the attempted text-mining approaches and other considerations regarding the manual curation of the data are pointed out, reflecting about the future automation of this type of reconstruction as means to widen the scope of analysis.

A network perspective on antimicrobial peptide combination therapies: the potential of colistin, polymyxin B and nisin

Antimicrobial combinations involving antimicrobial peptides (AMPs) attract considerable attention within current antimicrobial and anti-resistance research. The objective of this study was to review the available scientific literature on the effects of antimicrobial combinations involving colistin (polymyxin E), polymyxin B and nisin, which are US Food and Drug Administration (FDA)-approved AMPs broadly tested against prominent multidrug-resistant pathogens. A bioinformatics approach based on literature mining and manual expert curation supported the reconstruction of experimental evidence on the potential of these AMP combinations, as described in the literature. Network analysis enabled further characterisation of the retrieved antimicrobial agents, targets and combinatory effects. This systematic analysis was able to output valuable information on the studies conducted on colistin, polymyxin B and nisin combinations. The reconstructed networks enable the traversal and browsing of a large number of agent combinations, providing comprehensive details on the organisms, modes of growth and methodologies used in the studies. Therefore, network analysis enables a birds-eye view of current research trends as well as in-depth analysis of specific drugs, organisms and combinatory effects, according to particular user interests. The reconstructed knowledge networks are publicly accessible at http://sing-group.org/antimicrobialCombination/. Hopefully, this resource will help researchers to look into antimicrobial combinations more easily and systematically. User-customised queries may help identify missing and less studied links and to generate new research hypotheses.

Data Quality in Biofilm High-Throughput Routine Analysis: Intralaboratory Protocol Adaptation and Experiment Reproducibility.

Biofilm research is growing more diverse and dependent on high-throughput technologies, and the large-scale production of results aggravates data substantiation. In particular, experimental protocols are often adapted to meet the needs of a particular laboratory, and no statistical validation of the modified method is provided. This paper discusses the impact of intralaboratory adaptation and non-rigorous documentation of experimental protocols on biofilm data interchange and validation. The case study is a non-standard, but widely used, workflow for Pseudomonas aeruginosa biofilm development considering three analysis assays: the crystal violet (CV) assay for biomass quantification, the 2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide inner salt (XTT) assay for respiratory activity assessment, and the colony forming units (CFU) assay for determination of cell viability. The ruggedness of the protocol was assessed by introducing small changes in the biofilm growth conditions, which simulate minor protocol adaptations and non- rigorous protocol documentation. Results show that even minor variations in the biofilm growth conditions may affect the results considerably, and that the biofilm analysis assays lack repeatability. Intralaboratory validation of non-standard protocols is found critical to ensure data quality and enable the comparison of results within and among laboratories.

Exploring anti-quorum sensing and anti-virulence based strategies to fight Candida albicans infections: an in silico approach

The complex virulence attributes of Candida albicans are an attractive target to exploit in the development of new antifungals and anti-virulence strategies to combat C. albicans infections. Particularly, quorum sensing (QS) has been reported as critical for virulence regulation in C. albicans. This work presents two knowledge networks with up-to-date information about QS regulation and experimentally tested anti-QS and anti-virulence agents for C. albicans. A semi-automatic bioinformatics workflow that combines literature mining and expert curation was used to retrieve otherwise scattered information from the scientific literature. The network representation offers an innovative and continuously updatable means for the Candida research community to query QS and virulence data systematically and in a user-friendly way. Notably, the reconstructed networks show the complexity of QS regulation and the impact that some molecules have on the inhibition of virulence mechanisms responsible for infection establishment (e.g. hyphal development) and perseverance (e.g. biofilm formation). In the future, the compiled knowledge may be used to build decision-making models that help infer new knowledge of practical significance. The knowledge networks are publicly available at http://pcquorum.org/. This Web platform enables the exploration of fungal virulence cues as well as reported inhibitors in a user-friendly fashion.