scholarly journals Computational Prediction of Bacteriophage Host Ranges

2022 ◽  
Vol 10 (1) ◽  
pp. 149
Author(s):  
Cyril J. Versoza ◽  
Susanne P. Pfeifer
Keyword(s):  
Antibiotic Resistance ◽  
Host Range ◽  
High Throughput ◽  
Gold Standard ◽  
Computational Prediction ◽  
Bioinformatic Tools ◽  
Key Factor

Increased antibiotic resistance has prompted the development of bacteriophage agents for a multitude of applications in agriculture, biotechnology, and medicine. A key factor in the choice of agents for these applications is the host range of a bacteriophage, i.e., the bacterial genera, species, and strains a bacteriophage is able to infect. Although experimental explorations of host ranges remain the gold standard, such investigations are inherently limited to a small number of viruses and bacteria amendable to cultivation. Here, we review recently developed bioinformatic tools that offer a promising and high-throughput alternative by computationally predicting the putative host ranges of bacteriophages, including those challenging to grow in laboratory environments.

scholarly journals ε2-Phages Are Naturally Bred and Have a Vastly Improved Host Range in Staphylococcus aureus over Wild Type Phages

2021 ◽  
Vol 14 (4) ◽  
pp. 325
Author(s):  
David Sáez Moreno ◽  
Zehra Visram ◽  
Michele Mutti ◽  
Marcela Restrepo-Córdoba ◽  
Susana Hartmann ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Antibiotic Resistance ◽  
Detection Limit ◽  
Host Range ◽  
Alternative Treatment ◽  
Standard Of Care ◽  
Wild Type ◽  
Rapid Spread ◽  
Pharmaceutical Properties ◽  
Human Infections

Due to the rapid spread of antibiotic resistance, and the difficulties of treating biofilm-associated infections, alternative treatments for S. aureus infections are urgently needed. We tested the lytic activity of several wild type phages against a panel of 110 S. aureus strains (MRSA/MSSA) composed to reflect the prevalence of S. aureus clonal complexes in human infections. The plaquing host ranges (PHR) of the wild type phages were in the range of 51% to 60%. We also measured what we called the kinetic host range (KHR), i.e., the percentage of strains for which growth in suspension was suppressed for 24 h. The KHR of the wild type phages ranged from 2% to 49%, substantially lower than the PHRs. To improve the KHR and other key pharmaceutical properties, we bred the phages by mixing and propagating cocktails on a subset of S. aureus strains. These bred phages, which we termed evolution-squared (ε2) phages, have broader KHRs up to 64% and increased virulence compared to the ancestors. The ε2-phages with the broadest KHR have genomes intercrossed from up to three different ancestors. We composed a cocktail of three ε2-phages with an overall KHR of 92% and PHR of 96% on 110 S. aureus strains and called it PM-399. PM-399 has a lower propensity to resistance formation than the standard of care antibiotics vancomycin, rifampicin, or their combination, and no resistance was observed in laboratory settings (detection limit: 1 cell in 1011). In summary, ε2-phages and, in particular PM-399, are promising candidates for an alternative treatment of S. aureus infections.

scholarly journals High throughput functional variant screens via in-vivo production of single-stranded DNA

2020 ◽  
Author(s):  
Max G. Schubert ◽  
Daniel B. Goodman ◽  
Timothy M. Wannier ◽  
Divjot Kaur ◽  
Fahim Farzadfard ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
High Throughput ◽  
Entire Genome ◽  
Single Stranded Dna ◽  
Functional Variant ◽  
Continuous Generation ◽  
Sources Of Variation ◽  
Targeted Deep Sequencing ◽  
High Throughput Screens

AbstractTremendous genetic variation exists in nature, but our ability to create and characterize individual genetic variants remains far more limited in scale. Likewise, engineering proteins and phenotypes requires the introduction of synthetic variants, but design of variants outpaces experimental measurement of variant effect. Here, we optimize efficient and continuous generation of precise genomic edits in Escherichia coli, via in-vivo production of single-stranded DNA by the targeted reverse-transcription activity of retrons. Greater than 90% editing efficiency can be obtained using this method, enabling multiplexed applications. We introduce Retron Library Recombineering (RLR), a system for high-throughput screens of variants, wherein the association of introduced edits with their retron elements enables a targeted deep sequencing phenotypic output. We use RLR for pooled, quantitative phenotyping of synthesized variants, characterizing antibiotic resistance alleles. We also perform RLR using sheared genomic DNA of an evolved bacterium, experimentally querying millions of sequences for antibiotic resistance variants. In doing so, we demonstrate that RLR is uniquely suited to utilize non-designed sources of variation. Pooled experiments using ssDNA produced in vivo thus present new avenues for exploring variation, both designed and not, across the entire genome.

scholarly journals Human body-fluid proteome: quantitative profiling and computational prediction

2020 ◽  
Author(s):  
Lan Huang ◽  
Dan Shao ◽  
Yan Wang ◽  
Xueteng Cui ◽  
Yufei Li ◽  
...  
Keyword(s):  
High Throughput ◽  
Human Body ◽  
Body Fluid ◽  
Biomarker Discovery ◽  
Interaction Network ◽  
Computational Prediction ◽  
Computational Effort ◽  
The Body ◽  
Support Vector ◽  
Learning Approaches

Abstract Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein–protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

scholarly journals High-throughput investigation of crystal-to-glass transformation of Ti–Ni–Cu ternary alloy

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jian Hui ◽  
Haiqian Ma ◽  
Zheyu Wu ◽  
Zhan Zhang ◽  
Yang Ren ◽  
...  
Keyword(s):  
Glass Transition ◽  
Solid State ◽  
High Throughput ◽  
Solid State Reaction ◽  
Ion Beam ◽  
Ion Beam Sputtering ◽  
X Ray ◽  
Layer Sequence ◽  
Before And After ◽  
Key Factor

AbstractA high-throughput investigation of metallic glass formation via solid-state reaction was reported in this paper. Combinatorial multilayered thin-film chips covering the entire Ti–Ni–Cu ternary system were prepared using ion beam sputtering technique. Microbeam synchrotron X-ray diffraction (XRD) and X-ray fluorescence (XRF) measurements were conducted, with 1,325 data points collected from each chip, to map out the composition and the phase constitution before and after annealing at 373 K for 110 hours. The composition dependence of the crystal-to-glass transition by solid-state reaction was surveyed using this approach. The resulting composition–phase map is consistent with previously reported results. Time-of-flight secondary ion mass spectroscopy (ToF-SIMS) was performed on the representative compositions to determine the inter-diffusion between layers, the result shows that the diffusion of Ti is the key factor for the crystal-to-glass transition. In addition, both layer thickness and layer sequence play important roles as well. This work demonstrates that combinatorial chip technique is an efficient way for systematic and rapid study of crystal-to-glass transition for multi-component alloy systems.

scholarly journals Effects of Antibiotics on the Bacterial Community, Metabolic Functions and Antibiotic Resistance Genes in Mariculture Sediments during Enrichment Culturing

2020 ◽  
Vol 8 (8) ◽  
pp. 604
Author(s):  
Meng-Qi Ye ◽  
Guan-Jun Chen ◽  
Zong-Jun Du
Keyword(s):  
Antibiotic Resistance ◽  
Bacterial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
High Throughput ◽  
Antibiotic Resistance Genes ◽  
Control Group ◽  
Rrna Gene ◽  
Metabolic Functions ◽  
Culture Dependent

The effect of antibiotics on the diversity and functioning of indigenous microorganisms in the environment has attracted much attention. In this study, effects of exposure to six different antibiotics on the bacterial community, metabolic functions and antibiotic resistance genes (ARGs) in marine sediments during enrichment culturing were investigated. Classical culture-dependent method and high-throughput 16S rRNA gene sequencing method were both applied. In the culture-dependent analysis, the obtained 1549 isolates belonged to four phyla (Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria) and 155 genera. Proteobacteria and Firmicutes were the dominant phyla. The diversity and abundance of obtained bacteria after antibiotic processing exhibited different degrees of decrease. Enrichment culturing for different time could also affect the bacterial community composition. Some genera of bacteria were not isolated in the control group, but they could be isolated in the antibiotic-treated groups. In high-throughput 16S rRNA gene amplicon sequencing analyses, all the effective reads were clustered into 2822 OTUs at 97% similarity cutoff; they were annotated to 49 phyla, 103 class, 220 orders, 347 families, 624 genera and 1122 species. An alpha diversity analysis indicated that the community diversity and richness decreased under antibiotic exposure. The changes at the genus level were much more obvious. Only 48 genera of 129 genera were shared by all the samples. A total of 29 genera which were not detected in the initial control sample could be detected in at least one antibiotic-treated group. SIMPER analysis showed that OTU2543 and OTU1450 were the most common taxa to the dissimilarity of bacterial community between antibiotic-treated groups and the control group. OTU2034 and OUT2543 were the most contributive taxa to dissimilarity of groups incubating for different time. Metabolism was the predominant bacterial function. A total of 30 ARGs were detected in the samples. This study mainly focused on the changes of microbiota under the selective pressure of antibiotics for different time and the results demonstrated that the antibiotic could affect the bacterial diversity and richness in the marine ecosystem.

Four new derivatives of the broad-host-range cloning vector pBBR1MCS, carrying different antibiotic-resistance cassettes

Gene ◽  
1995 ◽  
Vol 166 (1) ◽  
pp. 175-176 ◽  
Author(s):  
Michael E. Kovach ◽  
Philip H. Elzer ◽  
D. Steven Hill ◽  
Gregory T. Robertson ◽  
Michael A. Farris ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Host Range ◽  
Cloning Vector ◽  
Broad Host Range ◽  
Derivatives Of
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