Kearney, C. M. | Search bioRxiv

bioRxiv2021

In vitro inhibition of H. pylori in a preferential manner using bioengineered L. lactis releasing guided Antimicrobial peptides

ObjectivesTargeted therapies seek to selectively eliminate a pathogen without disrupting the resident microbial community. This is even more important when a pathogen like H. pylori resides in stomach, a sensitive microbial ecosystem. Using a probiotic like Lactococcus lactis and bioengineering it to release a guided Antimicrobial Peptide (AMP) targeted towards the pathogen offers a pathway to specifically knock-out the deleterious species and not disturbing the stomach microbiome. ResultsThree AMPs, Alyteserin, CRAMP and Laterosporulin, were genetically fused to a guiding peptide MM1, which selectively binds to Vacuolating Toxin A (VacA) of H. pylori and cloned into an excretory vector pTKR inside L. lactis. When cultured together in vitro, the L. lactis bioengineered with guided AMPs selectively killed H. pylori when compared to E. coli or Lactobacillus plantarum, as determined by qPCR. Chemically synthesized Alyteserin and MM1-Alyteserin showed similar preferential inhibition of H. pylori when compared against E. coli, with the MIC of MM1-Alyteserin becoming significantly higher for E. coli than Alytserin whereas no such effet was observed against H. pylori. ConclusionsProbiotics bioengineered to excrete guided AMPs can be a novel and useful approach for combating pathogens without endangering the natural microbial flora. Given the wealth of AMPs and guiding ligands, both natural and synthetic, this approach can be adapted to develop a diverse array of chimeric guided AMPs and can be cloned into probiotics to create a safe and effective alternative to conventional chemical antibiotics.

molecular biology↗

bioRxiv2021

In situ treatment of H. pylori infection in mice stomach with bioengineered probiotic bacteria releasing guided Antimicrobial peptides

ObjectivesTargeted therapies seek to selectively eliminate a pathogen without disrupting the resident microbial community. This is even more important when a pathogen like H. pylori resides in stomach, a sensitive microbial ecosystem. Using a probiotic like Lactococcus lactis and bioengineering it to release a guided Antimicrobial Peptide (AMP) targeted towards the pathogen offers a pathway to specifically knock-out the deleterious species and not disturbing the stomach microbiome. ResultsThree AMPs, Alyteserin, CRAMP and Laterosporulin, were genetically fused to a guiding peptide MM1, which selectively binds to Vacuolating Toxin A (VacA) of H. pylori and cloned into an excretory vector pTKR inside L. lactis. When cultured together in vitro, the L. lactis bioengineered with guided AMPs selectively killed H. pylori when compared to E. coli or Lactobacillus plantarum, as determined by qPCR. Chemically synthesized Alyteserin and MM1-Alyteserin showed similar preferential inhibition of H. pylori when compared against E. coli, with the MIC of MM1-Alyteserin becoming significantly higher for E. coli than Alytserin whereas no such effet was observed against H. pylori. ConclusionsProbiotics bioengineered to excrete guided AMPs can be a novel and useful approach for combating pathogens without endangering the natural microbial flora. Given the wealth of AMPs and guiding ligands, both natural and synthetic, this approach can be adapted to develop a diverse array of chimeric guided AMPs and can be cloned into probiotics to create a safe and effective alternative to conventional chemical antibiotics.

molecular biology↗

bioRxiv2019

Making plants into cost-effective bioreactors for highly active antimicrobial peptides

As antibiotic-resistant bacterial pathogens become an ever-increasing concern, antimicrobial peptides (AMPs) have grown increasingly attractive as alternatives. Potentially, plants could be used as cost-effective AMP bioreactors; however, reported heterologous AMP expression is much lower in plants compared to E. coli expression systems and often results in plant cytotoxicity, even for AMPs fused to carrier proteins. We wondered if there were a physical factor that made heterologous AMPs difficult to express in plants. Using a meta-analysis of protein databases, we determined that native plant AMPs were significantly less cationic than AMPs native to other taxa. To apply this finding to plant expression, we tested the transient expression of 10 different heterologous AMPs, ranging in charge from +7 to -5, in the the tobacco, Nicotiana benthamiana. We first tested several carrier proteins and were able to express AMPs only with elastin-like polypeptide (ELP). Conveniently, ELP fusion allows for a simple, cost-effective temperature shift purification. Using the ELP system, all five anionic AMPs expressed well, with two at unusually high levels (375 and 563 {micro}g/gfw). Furthermore, antimicrobial activity against Staphylococcus epidermidis was an order of magnitude stronger (average MIC = 0.26 {micro}M) than that typically seen for AMPs expressed in E. coli expression systems. Unexpectedly, this high level of antimicrobial activity was associated with the uncleaved fusion peptide. In contrast, all previous reports of AMPs expressed in both plant and E. coli expression systems show cleavage from the fusion partner to be required before activity is seen. In summary, we describe a means of expressing AMP fusions in plants in high yield, purified with a simple temperature-shift protocol, resulting in a fusion peptide with high antimicrobial activity, without the need for a peptide cleavage step.

plant biology↗

bioRxiv2019

The use of a virus-derived targeting peptide to selectively kill staphylococcus bacteria with antimicrobial peptides

BackgroundTargeted therapies seek to selectively eliminate a pathogen without disrupting the microbiome community. Bacteriophages provide a rich, well-documented source of bacterium-specific binding proteins for use as targeting peptides fused to antimicrobial peptides. Though resistance may develop as with any antibiotic, the wealth of variants available in natural bacteriophage populations adds to the robustness of this system.\n\nResultsHere, we target two cationic antimicrobial peptides (AMPs), plectasin and eurocin, by genetically fusing their coding sequence to that of the host-binding protein of bacteriophage A12C, which selectively infects Staphylococcus. Surprisingly, we noted that targeting brought no change in the toxicity of the AMP when applied to two different staphylococci, S. aureus and S. epidermidis, but found a drastic decrease in toxicity against the negative controls, Enterococcus faecalis and Bacillus subtilis. Thus, the differential selectivity in this case is a loss of toxicity against the non-target species rather than the gain of toxicity against the target species which was reported in previous studies with other types of targeting antimicrobial peptides.\n\nConclusionThis is the first report of the use of virus-derived peptide sequences to target antimicrobial peptides. Considering the very large databank of bacteriophages and their bacterial hosts, this targeting approach should be generally applicable to a wide range of bacterial pathogens.

molecular biology↗

bioRxiv2017

Protein classification using modified n-gram and skip-gram models

MotivationClassification by supervised machine learning greatly facilitates the annotation of protein characteristics from their primary sequence. However, the feature generation step in this process requires detailed knowledge of attributes used to classify the proteins. Lack of this knowledge risks the selection of irrelevant features, resulting in a faulty model. In this study, we introduce a means of automating the work-intensive feature generation step via a Natural Language Processing (NLP)-dependent model, using a modified combination of N-Gram and Skip-Gram models (m-NGSG).\n\nResultsA meta-comparison of cross validation accuracy with twelve training datasets from nine different published studies demonstrates a consistent increase in accuracy of m-NGSG when compared to contemporary classification and feature generation models. We expect this model to accelerate the classification of proteins from primary sequence data and increase the accessibility of protein prediction to a broader range of scientists.\n\nAvailabilitym-NGSG is freely available at Bitbucket: https://bitbucket.org/smislam/mngsg/src\n\nSupplementslink to supplementary documents\n\nContactErich_Baker@baylor.edu

bioinformatics↗