Expanding the diversity of mycobacteriophages: insights into genome architecture and evolution.

Mycobacteriophages are viruses that infect mycobacterial hosts such as Mycobacterium smegmatis and Mycobacterium tuberculosis. All mycobacteriophages characterized to date are dsDNA tailed phages, and have either siphoviral or myoviral morphotypes. However, their genetic diversity is considerable, and although sixty-two genomes have been sequenced and comparatively analyzed, these likely represent only a small portion of the diversity of the mycobacteriophage population at large. Here we report the isolation, sequencing and comparative genomic analysis of 18 new mycobacteriophages isolated from geographically distinct locations within the United States. Although no clear correlation between location and genome type can be discerned, these genomes expand our knowledge of mycobacteriophage diversity and enhance our understanding of the roles of mobile elements in viral evolution. Expansion of the number of mycobacteriophages grouped within Cluster A provides insights into the basis of immune specificity in these temperate phages, and we also describe a novel example of apparent immunity theft. The isolation and genomic analysis of bacteriophages by freshman college students provides an example of an authentic research experience for novice scientists

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Exiguobacterium sp. is endowed with antibiotic properties against Gram positive and negative bacteria

Abstract Objective In order to isolate and identify bacteria that produce potentially novel bactericidal/bacteriostatic compounds, two ponds on the campus of the Rochester Institute of Technology (RIT) were targeted as part of a bioprospecting effort. Results One of the unique isolates, RIT 452 was identified as Exiguobacterium sp. and subjected to whole-genome sequencing. The genome was assembled and in silico analysis was performed to predict the secondary metabolite gene clusters, which suggested the potential of Exiguobacterium RIT452 for producing antibiotic compounds. Extracts of spent growth media of RIT452 were active in disc diffusion assays performed against four reference strains, two Gram-negative (E. coli ATCC 25922 and P. aeruginosa ATCC 27853) and two Gram-positive (B. subtilis BGSC 168 and S. aureus ATCC 25923). Differential extraction and liquid chromatography was used to fractionate the extracts. Efforts to identify and elucidate the structure of the active compound(s) are still ongoing

AI3SD Video: Skills4Scientists - Poster & Careers Symposium - Poster Compilation

This video forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD students. This video is a compilation of posters presented at the Skills4Scientists Posters & Careers Symposium. These poster presentations are predominantly from summer students involved in the AI3SD 2021 summer internship program. Higher resolution versions of the posters are available on the poster symposium website: https://www.ai3sd.org/s4s-symposium20...Not all poster presenters requested a recording of their talk. The following posters recordings are included in this compilation video. Poster 1 - Nearer the nearsightedness principle: Large-scale quantum chemical calculations – Andras Vekassy (University of Southampton) Poster 3 - Combining Ultrasonic Methods and Machine Learning Techniques to Assess Baked Products Quality – Erhan Gulsen (University of Nottingham) Poster 4 - Interactive Knowledge-Based Solvent Selection Tool – Hewan Zewdu (University of Nottingham)Poster 5 - CV in High Throughput Chemistry – Jamie Longino (University of Strathclyde)Poster 9 - Dewetting in Thin Liquid Films: Using Sparse Optimization to Learn Evolution Equations – Aspen Fenzl (University of Sheffield)Poster 12 - Creating a merged dataset and its exploration with different Machine Learning algorithms – Maximilian Hoffman (Freie Universität of Berlin)Poster 14 - Bayesian optimisation in Chemistry – Rubaiyat Khondaker (University of Cambridge) Poster 15 - A deep neural network for generation of functional organic materials – Rhyan Barrett (University of Warwick) Thank you to our sponsors Optibrium (https://www.optibrium.com/) and Dotmatics (https://www.dotmatics.com/) who supported this event. These poster presentations were live cartooned by ErrantScience (errantscience.com) which is also available on our YouTube Channel. Sections Intro: (0:00) Andras Vekassy - Nearer the nearsighted principle: Large-scale quantum chemical calculations: (0:17) Erhan Gulsen - Combining Ultrasonic Methods and Machine Learning Techniques to Assess Baked Products Quality: (06:11) Hewan Zewdu - Interactive Knowledge-Based Solvent Selection Tool: (12:09) Jamie Longino - CV in High Throughput Chemistry: (16:52) Aspen Fenzl - Dewetting in Thin Liquid Films: Using Sparse Optimization to Learn Evolution Equations: (21:21) Maximillian Hoffman - Creating a merged dataset and its exploration with different machine learning algorithms: (27:31) Rubaiyat Khondaker - Bayesian optimisation in Chemistry: (34:33) Rhyan Barrett - A deep neural network for generation of functional organic materials: (40:06) Further details from this series can be found at: https://www.ai3sd.org/skills4scientists This video is an output from the AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) which is funded by EPSRC under Grant Number EP/S000356/1 and PSDS (Physical Sciences Data science Service) which is funded by EPSRC under Grant Number EP/S020357/1

Supplementary Table S2 from Design and Evaluation of ZD06519, a Novel Camptothecin Payload for Antibody Drug Conjugates

Supplementary Table S2 shows the light stability of free drugs</p

Characterization of ADCs from Design and Evaluation of ZD06519, a Novel Camptothecin Payload for Antibody Drug Conjugates

HPLC-HIC, LC-MS, HPLC-SEC, residual free drug analysis, and endotoxin levels of ADCs</p

Synthetic Procedures from Design and Evaluation of ZD06519, a Novel Camptothecin Payload for Antibody Drug Conjugates

Synthesis and characterization of free drugs and drug-linkers</p

Supplementary Figure S2 from Design and Evaluation of ZD06519, a Novel Camptothecin Payload for Antibody Drug Conjugates

Supplementary Figure S2 shows the chemical stability of FD1 (ZD06519)</p

Supplementary Figure S4 from Design and Evaluation of ZD06519, a Novel Camptothecin Payload for Antibody Drug Conjugates

Supplementary Figure S4 shows the pharmacokinetic analysis of ADCs (total antibody PK) from the tolerability study in rats</p