Integrating Low-Order and High-Order Correlation Information for Identifying Phage Virion Proteins

Phage virion proteins (PVPs) play an important role in the host cell. Fast and accurate identification of PVPs is beneficial for the discovery and development of related drugs. Although wet experimental approaches are the first choice to identify PVPs, they are costly and time-consuming. Thus, researchers have turned their attention to computational models, which can speed up related studies. Therefore, we proposed a novel machine-learning model to identify PVPs in the current study. First, 50 different types of physicochemical properties were used to denote protein sequences. Next, two different approaches, including Pearson's correlation coefficient (PCC) and maximal information coefficient (MIC), were employed to extract discriminative information. Further, to capture the high-order correlation information, we used PCC and MIC once again. After that, we adopted the least absolute shrinkage and selection operator algorithm to select the optimal feature subset. Finally, these chosen features were fed into a support vector machine to discriminate PVPs from phage non-virion proteins. We performed experiments on two different datasets to validate the effectiveness of our proposed method. Experimental results showed a significant improvement in performance compared with state-of-the-art approaches. It indicates that the proposed computational model may become a powerful predictor in identifying PVPs.

Engineered Phage-Based Cancer Vaccines: Current Advances and Future Directions

Bacteriophages have emerged as versatile tools in the field of bioengineering, with enormous potential in tissue engineering, vaccine development, and immunotherapy. The genetic makeup of phages can be harnessed for the development of novel DNA vaccines and antigen display systems, as they can provide a highly organized and repetitive presentation of antigens to immune cells. Bacteriophages have opened new possibilities for the targeting of specific molecular determinants of cancer cells. Phages can be used as anticancer agents and carriers of imaging molecules and therapeutics. In this review, we explored the role of bacteriophages and bacteriophage engineering in targeted cancer therapy. The question of how the engineered bacteriophages can interact with the biological and immunological systems is emphasized to comprehend the underlying mechanism of phage use in cancer immunotherapy. The effectiveness of phage display technology in identifying high-affinity ligands for substrates, such as cancer cells and tumor-associated molecules, and the emerging field of phage engineering and its potential in the development of effective cancer treatments are discussed. We also highlight phage usage in clinical trials as well as the related patents. This review provides a new insight into engineered phage-based cancer vaccines.

A highly sensitive and ecofriendly assay platform for the simultaneous electrochemical determination of rifampicin and isoniazid in human serum and pharmaceutical formulations

Simple fabrication of an electrochemical sensor for simultaneous determination of rifampicin and isoniazid based on electrochemical modification of SPCE surface with reduced graphene oxide and nickel hydroxide film (Ni(OH)2/rGO/SPCE) without using toxic chemical agents.

A microfluidic device and instrument prototypes for the detection of Escherichia coli in water samples using a phage-based bioluminescence assay

Current quantification methods of Escherichia coli (E. coli) contamination in water samples involve long incubation, laboratory equipment and facilities, or complex processes that require specialized training for accurate operation and interpretation. To address these limitations, we have developed a microfluidic device and portable instrument prototypes capable of performing a rapid and highly sensitive bacteriophage-based assay to detect E. coli cells with detection limit comparable to traditional methods in a fraction of the time. The microfluidic device combines membrane filtration and selective enrichment using T7-NanoLuc-CBM, a genetically engineered bacteriophage, to identify 4.1 E. coli CFU in 100 mL of drinking water within 5.5 hours. The microfluidic device was designed and tested to process up to 100 mL of real-world drinking water samples with turbidities below 10 NTU. Prototypes of custom instrumentation, compatible with our valveless microfluidic device and capable of performing all of the assay's units of operation with minimal user intervention, demonstrated similar assay performance to that obtained on the benchtop assay. This research is the first step towards a faster, portable, and semi-automated, phage-based microfluidic platform for improved in-field water quality monitoring in low-resource settings.

Review of Label-Free Monitoring of Bacteria: From Challenging Practical Applications to Basic Research Perspectives

Novel biosensors already provide a fast way to detect the adhesion of whole bacteria (or parts of them), biofilm formation, and the effect of antibiotics. Moreover, the detection sensitivities of recent sensor technologies are large enough to investigate molecular-scale biological processes. Usually, these measurements can be performed in real time without using labeling. Despite these excellent capabilities summarized in the present work, the application of novel, label-free sensor technologies in basic biological research is still rare; the literature is dominated by heuristic work, mostly monitoring the presence and amount of a given analyte. The aims of this review are (i) to give an overview of the present status of label-free biosensors in bacteria monitoring, and (ii) to summarize potential novel directions with biological relevancies to initiate future development. Optical, mechanical, and electrical sensing technologies are all discussed with their detailed capabilities in bacteria monitoring. In order to review potential future applications of the outlined techniques in bacteria research, we summarize the most important kinetic processes relevant to the adhesion and survival of bacterial cells. These processes are potential targets of kinetic investigations employing modern label-free technologies in order to reveal new fundamental aspects. Resistance to antibacterials and to other antimicrobial agents, the most important biological mechanisms in bacterial adhesion and strategies to control adhesion, as well as bacteria-mammalian host cell interactions are all discussed with key relevancies to the future development and applications of biosensors.

Formulations for Bacteriophage Therapy and the Potential Uses of Immobilization

The emergence of antibiotic-resistant pathogens is becoming increasingly problematic in the treatment of bacterial diseases. This has led to bacteriophages receiving increased attention as an alternative form of treatment. Phages are effective at targeting and killing bacterial strains of interest and have yielded encouraging results when administered as part of a tailored treatment to severely ill patients as a last resort. Despite this, success in clinical trials has not always been as forthcoming, with several high-profile trials failing to demonstrate the efficacy of phage preparations in curing diseases of interest. Whilst this may be in part due to reasons surrounding poor phage selection and a lack of understanding of the underlying disease, there is growing consensus that future success in clinical trials will depend on effective delivery of phage therapeutics to the area of infection. This can be achieved using bacteriophage formulations instead of purely liquid preparations. Several encapsulation-based strategies can be applied to produce phage formulations and encouraging results have been observed with respect to efficacy as well as long term phage stability. Immobilization-based approaches have generally been neglected for the production of phage therapeutics but could also offer a viable alternative.

Phage display as a tool for vaccine and immunotherapy development

Bacteriophages, or phages, are viruses that specifically infect bacteria and coopt the cellular machinery to create more phage proteins, eventually resulting in the release of new phage particles. Phages are heavily utilized in bioengineering for applications ranging from tissue engineering scaffolds to immune signal delivery. Of specific interest to vaccines and immunotherapies, phages have demonstrated an ability to activate both the innate and adaptive immune systems. The genome of these viral particles can be harnessed for DNA vaccination, or the surface proteins can be exploited for antigen display. More specifically, genes that encode an antigen of interest can be spliced into the phage genome, allowing antigenic proteins or peptides to be displayed by fusion to phage capsid proteins. Phages therefore present antigens to immune cells in a highly ordered and repetitive manner. This review discusses the use of phage with adjuvanting activity as antigen delivery vehicles for vaccination against infectious disease and cancer.

Pred-BVP-Unb: Fast prediction of bacteriophage Virion proteins using un-biased multi-perspective properties with recursive feature elimination

Bacteriophage virion proteins (BVPs) are bacterial viruses that have a great impact on different biological functions of bacteria. They are significantly used in genetic engineering and phage therapy applications. Correct identification of BVP through conventional pathogen methods are slow and expensive. Thus, designing a Bioinformatics predictor is urgently desirable to accelerate correct identification of BVPs within a huge volume of proteins. However, available prediction tools performance is inadequate due to the lack of useful feature representation and severe imbalance issue. In the present study, we propose an intelligent model, called Pred-BVP-Unb for discrimination of BVPs that employed three nominal sequences-driven descriptors, i.e. Bi-PSSM evolutionary information, composition & translation, and split amino acid composition. The imbalance phenomena between classes were coped with the help of a synthetic minority oversampling technique. The essential attributes are selected by a robust algorithm called recursive feature elimination. Finally, the optimal feature space is provided to support vector machine classifier using a radial base kernel in order to train the model. Our predictor remarkably outperforms than existing approaches in the literature by achieving the highest accuracy of 92.54% and 83.06% respectively on the benchmark and independent datasets. We expect that Pred-BVP-Unb tool can provide useful hints for designing antibacterial drugs and also helpful to expedite large scale discovery of new bacteriophage virion proteins. The source code and all datasets are publicly available at https://github.com/Muhammad-Arif-NUST/BVP_Pred_Unb.

Lytic KFS-SE2 phage as a novel bio-receptor for Salmonella Enteritidis detection

Since Salmonella Enteritidis is one of the major foodborne pathogens, on-site applicable rapid detection methods have been required for its control. The purpose of this study was to isolate and purify S. Enteritidis-specific phage (KFS-SE2 phage) from an eel farm and to investigate its feasibility as a novel, efficient, and reliable bio-receptor for its employment. KFS-SE2 phage was successfully isolated at a high concentration of (2.31 ± 0.43) × 10¹¹ PFU/ml, and consisted of an icosahedral head of 65.44 ± 10.08 nm with a non-contractile tail of 135.21 ± 12.41 nm. The morphological and phylogenetic analysis confirmed that it belongs to the Pis4avirus genus in the family of Siphoviridae. KFS-SE2 genome consisted of 48,608 bp with 45.7% of GC content. Genome analysis represented KFS-SE2 to have distinctive characteristics as a novel phage. Comparative analysis of KFS-SE2 phage with closely related strains confirmed its novelty by the presence of unique proteins. KFS-SE2 phage exhibited excellent specificity to S. Enteritidis and was stable under the temperature range of 4 to 50°C and pH of 3 to 11 (P < 0.05). The latent time was determined to be 20 min. Overall, a new lytic KFS-SE2 phage was successfully isolated from the environment at a high concentration and the excellent feasibility of KFS-SE2 phage was demonstrated as a new bio-receptor for S. Enteritidis detection.

Detection of Acidic Pharmaceutical Compounds Using Virus-Based Molecularly Imprinted Polymers

Molecularly imprinted polymers (MIPs) have proven to be particularly effective chemical probes for the molecular recognition of proteins, DNA, and viruses. Here, we started from a filamentous bacteriophage to synthesize a multi-functionalized MIP for detecting the acidic pharmaceutic clofibric acid (CA) as a chemical pollutant. Adsorption and quartz crystal microbalance with dissipation monitoring experiments showed that the phage-functionalized MIP had a good binding affinity for CA, compared with the non-imprinted polymer and MIP. In addition, the reusability of the phage-functionalized MIP was demonstrated for at least five repeated cycles, without significant loss in the binding activity. The results indicate that the exposed amino acids of the phage, together with the polymer matrix, create functional binding cavities that provide higher affinity to acidic pharmaceutical compounds.

Improved recovery of bacteriophage M13 using an ATPS-based bioprocess

Aqueous two-phase systems (ATPS) have been widely exploited for the recovery and partial purification of biological compounds. Recently our research group characterized the primary recovery and partial purification of bacteriophage M13 using polymer-salt and ionic liquid-salt ATPS. From such study, it was concluded that PEG 400-potassium phosphate ATPS with a volume ratio (V_R ) of 1 and 25% w/w TLL were the best suitable for the primary recovery of bacteriophage M13 from a crude extract, achieving a recovery yield of 83.3%. Although such system parameters were proven to be adequate for the recovery of the product of interest, it was concluded that further optimization was desirable and attainable by studying the effect of additional system parameters such as V_R , concentration of neutral salt (M) and sample load (% w/w). This research work presents an optimization of a previously reported process for the recovery of bacteriophage M13 directly from a crude extract using ATPS. The increase in V_R and sample load showed a positive effect in the recovery of M13 indicating an improved performance of the proposed ATPS. According to the results presented here, a system composed of PEG 400 17.2% (w/w), potassium phosphate 15.5% (w/w) and a sample load of 30% (w/w) allowed the recovery of M13 directly from a crude extract with a top phase recovery of 80.1%, representing an increase of 4.8 times in the final concentration and a reduction of 2.65 times in the processing costs. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 2018 © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1177-1184, 2018.

Recent advances in bacteriophage-based methods for bacteria detection

Fast and reliable bacteria detection is crucial for lowering the socioeconomic burden related to bacterial infections (e.g., in healthcare, industry or security). Bacteriophages (i.e., viruses with bacterial hosts) pose advantages such as great specificity, robustness, toughness and cheap preparation, making them popular biorecognition elements in biosensors and other assays for bacteria detection. There are several possible designs of bacteriophage-based biosensors. Here, we focus on developments based on whole virions as recognition agents. We divide the review into sections dealing with phage lysis as an analytical signal, phages as capturing elements in assays and phage-based sensing layers, putting the main focus on development reported within the past three years but without omitting the fundamentals.

Conformations and membrane-driven self-organization of rodlike fd virus particles on freestanding lipid membranes

Membrane-mediated interactions and aggregation of colloidal particles adsorbed to responsive elastic membranes are challenging problems relevant for understanding the microscopic organization and dynamics of biological membranes. We experimentally study the behavior of rodlike semiflexible fd virus particles electrostatically adsorbed to freestanding cationic lipid membranes and find that their behavior can be controlled by tuning the membrane charge and ionic strength of the surrounding medium. Three distinct interaction regimes of rodlike virus particles with responsive elastic membranes can be observed. (i) A weakly charged freestanding cationic lipid bilayer in a low ionic strength medium represents a gentle quasi-2D substrate preserving the integrity, structure, and mechanical properties of the membrane-bound semiflexible fd virus, which under these conditions is characterized by a monomer length of 884 ± 4 nm and a persistence length of 2.5 ± 0.2 μm, in perfect agreement with its properties in bulk media. (ii) An increase in the membrane charge leads to the membrane-driven collapse of fd virus particles on freestanding lipid bilayers and lipid nanotubes into compact globules. (iii) When the membrane charge is low, and the mutual electrostatic repulsion of membrane-bound virus particles is screened to a considerable degree, membrane-driven self-organization of membrane-bound fd virus particles into long linear tip-to-tip aggregates showing dynamic self-assembly/disassembly and quasi-semiflexible behavior takes place. These observations are in perfect agreement with the results of recent theoretical and simulation studies predicting that membrane-mediated interactions can control the behavior of colloidal particles adsorbed on responsive elastic membranes.

Emerging Microtechnologies and Automated Systems for Rapid Bacterial Identification and Antibiotic Susceptibility Testing

Rapid bacterial identification (ID) and antibiotic susceptibility testing (AST) are in great demand due to the rise of drug-resistant bacteria. Conventional culture-based AST methods suffer from a long turnaround time. By necessity, physicians often have to treat patients empirically with antibiotics, which has led to an inappropriate use of antibiotics, an elevated mortality rate and healthcare costs, and antibiotic resistance. Recent advances in miniaturization and automation provide promising solutions for rapid bacterial ID/AST profiling, which will potentially make a significant impact in the clinical management of infectious diseases and antibiotic stewardship in the coming years. In this review, we summarize and analyze representative emerging micro- and nanotechnologies, as well as automated systems for bacterial ID/AST, including both phenotypic (e.g., microfluidic-based bacterial culture, and digital imaging of single cells) and molecular (e.g., multiplex PCR, hybridization probes, nanoparticles, synthetic biology tools, mass spectrometry, and sequencing technologies) methods. We also discuss representative point-of-care (POC) systems that integrate sample processing, fluid handling, and detection for rapid bacterial ID/AST. Finally, we highlight major remaining challenges and discuss potential future endeavors toward improving clinical outcomes with rapid bacterial ID/AST technologies.

Dense Layer of Bacteriophages Ordered in Alternating Electric Field and Immobilized by Surface Chemical Modification as Sensing Element for Bacteria Detection

Faster and more sensitive environmental monitoring should be developed to face the worldwide problem of bacterial infections. To remedy this issue, we demonstrate a bacteria-sensing element that utilizes dense and ordered layers of bacteriophages specific to the given bacteria strain. We combine (1) the chemical modification of a surface to increase the surface coverage of bacteriophages (2) with an alternating electric field to greatly increase the number of properly oriented bacteriophages at the surface. Usually, in sensing elements, a random orientation of bacteriophages results in steric hindrance, which results in no more than a few percent of all receptors being available. An increased number of properly ordered phages results in the optimal performance of phage receptors, manifesting in up to a 64-fold increase in sensitivity and a limit of detection as low as 100 CFU mL^-1. Our sensing elements can be applied for selective, sensitive, and fast (15 min) bacterial detection. A well-studied pair T4 bacteriophage-bacteria Escherichia coli, was used as a model; however, the method could be adapted to prepare bacteriophage-based sensors for detection of a variety of bacterial strains.

Predicting bacteriophage proteins located in host cell with feature selection technique

A bacteriophage is a virus that can infect a bacterium. The fate of an infected bacterium is determined by the bacteriophage proteins located in the host cell. Thus, reliably identifying bacteriophage proteins located in the host cell is extremely important to understand their functions and discover potential anti-bacterial drugs. Thus, in this paper, a computational method was developed to recognize bacteriophage proteins located in host cells based only on their amino acid sequences. The analysis of variance (ANOVA) combined with incremental feature selection (IFS) was proposed to optimize the feature set. Using a jackknife cross-validation, our method can discriminate between bacteriophage proteins located in a host cell and the bacteriophage proteins not located in a host cell with a maximum overall accuracy of 84.2%, and can further classify bacteriophage proteins located in host cell cytoplasm and in host cell membranes with a maximum overall accuracy of 92.4%. To enhance the value of the practical applications of the method, we built a web server called PHPred (〈http://lin.uestc.edu.cn/server/PHPred〉). We believe that the PHPred will become a powerful tool to study bacteriophage proteins located in host cells and to guide related drug discovery.