A quick guide for student-driven community genome annotation

High quality gene models are necessary to expand the molecular and genetic tools available for a target organism, but these are available for only a handful of model organisms that have undergone extensive curation and experimental validation over the course of many years. The majority of gene models present in biological databases today have been identified in draft genome assemblies using automated annotation pipelines that are frequently based on orthologs from distantly related model organisms. Manual curation is time consuming and often requires substantial expertise, but is instrumental in improving gene model structure and identification. Manual annotation may seem to be a daunting and cost-prohibitive task for small research communities but involving undergraduates in community genome annotation consortiums can be mutually beneficial for both education and improved genomic resources. We outline a workflow for efficient manual annotation driven by a team of primarily undergraduate annotators. This model can be scaled to large teams and includes quality control processes through incremental evaluation. Moreover, it gives students an opportunity to increase their understanding of genome biology and to participate in scientific research in collaboration with peers and senior researchers at multiple institutions

Perceptions on artificial intelligence-based decision making for coexisting multiple long-term health conditions: A protocol for a qualitative study with patients and healthcare professionals

IntroductionCoexisting multiple health conditions is common among older people, a population that is increasing globally. The potential for polypharmacy, adverse events, drug interactions and causing additional health conditions complicates prescribing decisions for these patients. Artificial Intelligence (AI)-generated decision-making tools may help guide clinical decisions in the context of multiple health conditions, by determining which of multiple medication options is best. This study aims to explore the perceptions of healthcare professionals (HCPs) and patients on the use of AI in the management of multiple health conditions.Methods and analysis A qualitative study will be conducted using semi-structured interviews. Adults (≥18 years) with multiple health conditions living in the West Midlands of England and HCPs with experience in caring for patients with multiple health conditions will be eligible and purposively sampled. Patients will be identified from Clinical Practice Research Datalink (CPRD) Aurum; CPRD will contact general practitioners who will in turn, send a letter to patients inviting them to take part. Eligible HCPs will be recruited through British healthcare professional bodies and known contacts. Up to 30 patients and 30 HCPs will be recruited, until data saturation is achieved. Interviews will be in-person or virtual, audio recorded and transcribed verbatim. The topic guide was designed to explore participants’ attitudes towards AI-informed clinical decision-making to augment clinician-directed decision-making, the perceived advantages and disadvantages of both methods and attitudes toward risk management. Case vignettes comprising a common decision pathway for patients with multiple health conditions will be presented during each interview to invite participants’ opinions on how their experiences compare. Data will be analysed thematically using the Framework method.Ethics and dissemination This study has been approved by the National Health Service Research Ethics Committee (Reference: 22/SC/0210). Written informed consent or verbal consent will be obtained prior to each interview. The findings from this study will be disseminated through peer- reviewed publications, conferences and lay summaries.<br/

Using Tobamoviruses for Phylogenetic Instruction in Undergraduate Biology Courses

Microbial diversity and taxonomy instruction provide an ideal opportunity to introduce students to basic bioinformatics skills.  There are many ways to illustrate evolutionary relationships between microorganisms using phylogenetic trees. Thought must be given to the method of presentation used in class because interpreting complex trees can be quite challenging for students. Here we present a simple activity that teaches the fundamental bioinformatics skills of multiple sequence alignments and phylogenetics by using Tropical soda apple mosaic virus and other tobamoviruses that produce trees that are easy to interpret.  Tobamoviruses are important agricultural pathogens and have well defined phylogenetic groupings that correspond to the phylogenetic groupings of host plant families.  This clear pattern illustrates the coevolution of the virus and host, and makes interpreting relationships based on these trees very straightforward.  The organization of the trees also indicates related plants that a given virus may potentially infect, making this type of analysis useful for developing measures to limit spread and minimize economic impacts.  The simplicity of the analysis, coupled with the real-world application in agricultural science, helps actively engage students in a topic that is challenging to learn.  This activity is broadly adaptable, and can be introduced as a learning module in courses covering topics in microbiology, molecular biology, genetics and evolution.  Completion of this activity provides students with key foundational skills for phylogenetic analysis and the confidence to utilize bioinformatics software.

Isolation of Microbes from Lake Vostok Accretion Ice▿

Bacteria from seven Lake Vostok accretion and two deep glacial Vostok ice core sections were characterized. The cell concentrations were low, but many of the cells were viable. From the hundreds of cultures, 18 unique bacterial rRNA gene phylotypes were determined. Lake Vostok may contain a complex microbial ecosystem

Genomic diversity of bacteriophages infecting Microbacterium spp.

The bacteriophage population is vast, dynamic, old, and genetically diverse. The genomics of phages that infect bacterial hosts in the phylum Actinobacteria show them to not only be diverse but also pervasively mosaic, and replete with genes of unknown function. To further explore this broad group of bacteriophages, we describe here the isolation and genomic characterization of 116 phages that infect Microbacterium spp. Most of the phages are lytic, and can be grouped into twelve clusters according to their overall relatedness; seven of the phages are singletons with no close relatives. Genome sizes vary from 17.3 kbp to 97.7 kbp, and their G+C% content ranges from 51.4% to 71.4%, compared to ~67% for their Microbacterium hosts. The phages were isolated on five different Microbacterium species, but typically do not efficiently infect strains beyond the one on which they were isolated. These Microbacterium phages contain many novel features, including very large viral genes (13.5 kbp) and unusual fusions of structural proteins, including a fusion of VIP2 toxin and a MuF-like protein into a single gene. These phages and their genetic components such as integration systems, recombineering tools, and phage-mediated delivery systems, will be useful resources for advancing Microbacterium genetics

Instructional Models for Course-Based Research Experience (CRE) Teaching

The course-based research experience (CRE) with its documented educational benefits is increasingly being implemented in science, technology, engineering, and mathematics education. This article reports on a study that was done over a period of 3 years to explicate the instructional processes involved in teaching an undergraduate CRE. One hundred and two instructors from the established and large multi-institutional SEA-PHAGES program were surveyed for their understanding of the aims and practices of CRE teaching. This was followed by large-scale feedback sessions with the cohort of instructors at the annual SEA Faculty Meeting and subsequently with a small focus group of expert CRE instructors. Using a qualitative content analysis approach, the survey data were analyzed for the aims of inquiry instruction and pedagogical practices used to achieve these goals. The results characterize CRE inquiry teaching as involving three instructional models: 1) being a scientist and generating data; 2) teaching procedural knowledge; and 3) fostering project ownership. Each of these models is explicated and visualized in terms of the specific pedagogical practices and their relationships. The models present a complex picture of the ways in which CRE instruction is conducted on a daily basis and can inform instructors and institutions new to CRE teaching