An Introduction to Programming for Bioscientists: A Python-based Primer

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in the biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a 'variable', the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.Comment: 65 pages total, including 45 pages text, 3 figures, 4 tables, numerous exercises, and 19 pages of Supporting Information; currently in press at PLOS Computational Biolog

CRISPR-Cas9 ribonucleoprotein-mediated gene editing in the plant pathogenic fungus Magnaporthe oryzae

Magnaporthe oryzae, the cause of rice blast disease, is a model fungus for studying plant-pathogen interactions and a major threat to global agriculture. From changes made to their DNA, pathogens like M. oryzae have evolved characteristics like aggressiveness, host range, and fungicide resistance. Once source of DNA variation, arises from DNA repair. There are many sources of DNA damage, with the most severe being double-strand breaks (DSBs) which can lead to genome instability if left unrepaired. Hence, eukaryotes have evolved complex repair mechanisms like microhomology-mediated-end-joining (MMEJ), non-homologous-end-joining (NHEJ) and homologous-recombination (HR) to repair DNA DSBs. Interestingly, these repair pathways have different rates of fidelity, meaning some pathways create more mutations than others. In filamentous fungi, the mechanism by which MMEJ repairs DSBs is not well molecularly characterized, so the purpose of this project is to identify genes controlling MMEJ. To facilitate this, we created knockouts for homologs of DNA repair genes. Five genes were selected for deletion, including ligase 1 A & B, and polymerases θ, 3, and 4. Two CRISPR-Cas9 ribonucleoproteins were used to make DNA DSBs surrounding our target genes. Donor DNA encoding resistance to G418 antibiotic was supplied for insertion into the DSB site, where it served as a selectable marker when plated on complete media containing G418 antibiotics. DNA was extracted from individual colonies and used in PCR genotyping to test for the target gene and correct G418 integration. These knockouts will be characterized in future work to determine their individual roles in MMEJ DSB repair

Toward a Designable Extracellular Matrix: Molecular Dynamics Simulations of an Engineered Laminin-mimetic, Elastin-like Fusion Protein

Native extracellular matrices (ECMs), such as those of the human brain and other neural tissues, exhibit networks of molecular interactions between specific matrix proteins and other tissue components. Guided by these naturally self-assembling supramolecular systems, we have designed a matrix-derived protein chimera that contains a laminin globular-like (LG) domain fused to an elastin-like polypeptide (ELP). All-atom, classical molecular dynamics simulations of our designed laminin-elastin fusion protein reveal temperature-dependent conformational changes, in terms of secondary structure composition, solvent accessible surface area, hydrogen bonding, and surface hydration. These properties illuminate the phase behavior of this fusion protein, via the emergence of $\beta$-sheet character in physiologically-relevant temperature ranges.Comment: 53 pages, 7 figures in the main text; Supporting Information contains 1 table, 12 figures, 4 trajectory animations (videos

Modeling resilience and sustainability in ancient agricultural systems

The reasons why people adopt unsustainable agricultural practices, and the ultimate environmental implications of those practices, remain incompletely understood in the present world. Archaeology, however, offers unique datasets on coincident cultural and ecological change, and their social and environmental effects. This article applies concepts derived from ecological resilience thinking to assess the sustainability of agricultural practices as a result of long-term interactions between political, economic, and environmental systems. Using the urban center of Gordion, in central Turkey, as a case study, it is possible to identify mismatched social and ecological processes on temporal, spatial, and organizational scales, which help to resolve thresholds of resilience. Results of this analysis implicate temporal and spatial mismatches as a cause for local environmental degradation, and increasing extralocal economic pressures as an ultimate cause for the adoption of unsustainable land-use practices. This analysis suggests that a research approach that integrates environmental archaeology with a resilience perspective has considerable potential for explicating regional patterns of agricultural change and environmental degradation in the past

Nothing Lasts Forever: Environmental Discourses on the Collapse of Past Societies

The study of the collapse of past societies raises many questions for the theory and practice of archaeology. Interest in collapse extends as well into the natural sciences and environmental and sustainability policy. Despite a range of approaches to collapse, the predominant paradigm is environmental collapse, which I argue obscures recognition of the dynamic role of social processes that lie at the heart of human communities. These environmental discourses, together with confusion over terminology and the concepts of collapse, have created widespread aporia about collapse and resulted in the creation of mixed messages about complex historical and social processes

When here becomes there: attentional distribution modulates foveal bias in peripheral localization

Much research concerning attention has focused on changes in the perceptual qualities of objects while attentional states were varied. Here, we address a complementary question—namely, how perceived location can be altered by the distribution of sustained attention over the visual field. We also present a new way to assess the effects of distributing spatial attention across the visual field. We measured magnitude judgments relative to an aperture edge to test perceived location across a large range of eccentricities (30°), and manipulated spatial uncertainty in target locations to examine perceived location under three different distributions of spatial attention. Across three experiments, the results showed that changing the distribution of sustained attention significantly alters known foveal biases in peripheral localization