Production of 3D printed scale models from microscope volume datasets for use in STEM education

Understanding the three-dimensional morphology of a biological sample at the microscopic level is a prerequisite to a functional understanding of cell biology, tissue development and growth. Images of microscopic samples obtained by compound light microscopy are customarily recorded and represented in two dimensions from a single orientation making it difficult to extrapolate 3D context from the 2D information. The commercialisation of fast, laser-based microscope systems (e.g. confocal, multi-photon or lightsheet microscopy) capable of generating volume datasets of microscopic samples through optical sectioning, coupled with advances in computer technology allowing accurate volume rendering of these datasets, have facilitated significant improvement in our 3D understanding of the microscopic world in virtual space. The advent of affordable 3D printing technology now offers the prospect of generating morphologically accurate, physical models from these microscope volume datasets for use in science education, outreach and engagement. 3D printed scale replicas will provide improved sensory perception, offering tactile as well as visual interaction, leading to improved understanding of structure function relationships. Here we present a technique to reliably generate detailed, physical 3D models from Z-stacks of optical sections from confocal and lightsheet microscopes using affordable, entry-level 3D printing technology. We use the technique to generate 3D printed models of a variety of different biological samples at a range of scales including pollen grains from two species of plant; blood cells from both human and earthworm species, a section of plant root; the compound eye of an ant; and a developing Zebrafish larva; all of which have been used in our teaching, engagement and outreach activities. Our methods can, in principle, be used to generate 3D printed models from microscope volume datasets of any small fluorescent or reflective samples

Fostering Systems Research in Europe

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Impact of genomic testing and patient-reported outcomes on receipt of adjuvant chemotherapy

Practice guidelines incorporate genomic tumor profiling, using results such as the Oncotype DX Recurrence Score (RS), to refine recurrence risk estimates for the large proportion of breast cancer patients with early-stage, estrogen receptor-positive disease. We sought to understand the impact of receiving genomic recurrence risk estimates on breast cancer patients’ well-being and the impact of these patient-reported outcomes on receipt of adjuvant chemotherapy. Participants were 193 women (mean age 57) newly diagnosed with early-stage breast cancer. Women were interviewed before and 2–3 weeks after receiving the RS result between 2011 and 2015. We assessed subsequent receipt of chemotherapy from chart review. After receiving their RS, perceived pros (t = 4.27, P < .001) and cons (t = 8.54, P <.001) of chemotherapy increased from pre-test to post-test, while perceived risk of breast cancer recurrence decreased (t = 2.90, P = .004). Women with high RS tumors were more likely to receive chemotherapy than women with low RS tumors (88 vs. 5 %, OR 0.01, 0.00–0.02, P < .001). Higher distress (OR 2.19, 95 % CI 1.05–4.57, P < .05) and lower perceived cons of chemotherapy (OR 0.50, 95 % CI 0.26–0.97, P < .05) also predicted receipt of chemotherapy. Distressed patients who saw few downsides of chemotherapy received this treatment. Clinicians should consider these factors when discussing chemotherapy with breast cancer patients

Rational optimization of tolC as a powerful dual selectable marker for genome engineering

Selection has been invaluable for genetic manipulation, although counter-selection has historically exhibited limited robustness and convenience. TolC, an outer membrane pore involved in transmembrane transport in E. coli, has been implemented as a selectable/counter-selectable marker, but counter-selection escape frequency using colicin E1 precludes using tolC for inefficient genetic manipulations and/or with large libraries. Here, we leveraged unbiased deep sequencing of 96 independent lineages exhibiting counter-selection escape to identify loss-of-function mutations, which offered mechanistic insight and guided strain engineering to reduce counter-selection escape frequency by ∼40-fold. We fundamentally improved the tolC counter-selection by supplementing a second agent, vancomycin, which reduces counter-selection escape by 425-fold, compared colicin E1 alone. Combining these improvements in a mismatch repair proficient strain reduced counter-selection escape frequency by 1.3E6-fold in total, making tolC counter-selection as effective as most selectable markers, and adding a valuable tool to the genome editing toolbox. These improvements permitted us to perform stable and continuous rounds of selection/counter-selection using tolC, enabling replacement of 10 alleles without requiring genotypic screening for the first time. Finally, we combined these advances to create an optimized E. coli strain for genome engineering that is ∼10-fold more efficient at achieving allelic diversity than previous best practices

Enhanced multiplex genome engineering through co-operative oligonucleotide co-selection

Genome-scale engineering of living organisms requires precise and economical methods to efficiently modify many loci within chromosomes. One such example is the directed integration of chemically synthesized single-stranded deoxyribonucleic acid (oligonucleotides) into the chromosome of Escherichia coli during replication. Herein, we present a general co-selection strategy in multiplex genome engineering that yields highly modified cells. We demonstrate that disparate sites throughout the genome can be easily modified simultaneously by leveraging selectable markers within 500 kb of the target sites. We apply this technique to the modification of 80 sites in the E. coli genome.United States. Dept. of Energy. Genomes To Life (DE-FG02-03ER6344)National Science Foundation (U.S.). Genes and Genomes Systems Cluster (0719344)National Science Foundation (U.S.). Center for Bits and Atoms (0122419)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (0540879

Orthology Analysis and In Vivo Complementation Studies to Elucidate the Role of DIR1 during Systemic Acquired Resistance in Arabidopsis thaliana and Cucumis sativus

AtDIR1 (Defective in Induced Resistance1) is an acidic lipid transfer protein essential for systemic acquired resistance (SAR) in Arabidopsis thaliana. Upon SAR induction, DIR1 moves from locally infected to distant uninfected leaves to activate defense priming; however, a molecular function for DIR1 has not been elucidated. Bioinformatic analysis and in silico homology modeling identified putative AtDIR1 orthologs in crop species, revealing conserved protein motifs within and outside of DIR1’s central hydrophobic cavity. In vitro assays to compare the capacity of recombinant AtDIR1 and targeted AtDIR1-variant proteins to bind the lipophilic probe TNS (6,P-toluidinylnaphthalene-2-sulfonate) provided evidence that conserved leucine 43 and aspartic acid 39 contribute to the size of the DIR1 hydrophobic cavity and possibly hydrophobic ligand binding. An Arabidopsis–cucumber SAR model was developed to investigate the conservation of DIR1 function in cucumber (Cucumis sativus), and we demonstrated that phloem exudates from SAR-induced cucumber rescued the SAR defect in the Arabidopsis dir1-1 mutant. Additionally, an AtDIR1 antibody detected a protein of the same size as AtDIR1 in SAR-induced cucumber phloem exudates, providing evidence that DIR1 function during SAR is conserved in Arabidopsis and cucumber. In vitro TNS displacement assays demonstrated that recombinant AtDIR1 did not bind the SAR signals azelaic acid (AzA), glycerol-3-phosphate or pipecolic acid. However, recombinant CsDIR1 and CsDIR2 interacted weakly with AzA and pipecolic acid. Bioinformatic and functional analyses using the Arabidopsis–cucumber SAR model provide evidence that DIR1 orthologs exist in tobacco, tomato, cucumber, and soybean, and that DIR1-mediated SAR signaling is conserved in Arabidopsis and cucumber

Emergent rules for codon choice elucidated by editing rare arginine codons in Escherichia coli

The degeneracy of the genetic code allows nucleic acids to encode amino acid identity as well as noncoding information for gene regulation and genome maintenance. The rare arginine codons AGA and AGG (AGR) present a case study in codon choice, with AGRs encoding important transcriptional and translational properties distinct from the other synonymous alternatives (CGN). We created a strain of Escherichia coli with all 123 instances of AGR codons removed from all essential genes. We readily replaced 110 AGR codons with the synonymous CGU codons, but the remaining 13 “recalcitrant” AGRs required diversification to identify viable alternatives. Successful replacement codons tended to conserve local ribosomal binding site-like motifs and local mRNA secondary structure, sometimes at the expense of amino acid identity. Based on these observations, we empirically defined metrics for a multidimensional “safe replacement zone” (SRZ) within which alternative codons are more likely to be viable. To evaluate synonymous and nonsynonymous alternatives to essential AGRs further, we implemented a CRISPR/Cas9-based method to deplete a diversified population of a wild-type allele, allowing us to evaluate exhaustively the fitness impact of all 64 codon alternatives. Using this method, we confirmed the relevance of the SRZ by tracking codon fitness over time in 14 different genes, finding that codons that fall outside the SRZ are rapidly depleted from a growing population. Our unbiased and systematic strategy for identifying unpredicted design flaws in synthetic genomes and for elucidating rules governing codon choice will be crucial for designing genomes exhibiting radically altered genetic codes.United States. Department of Energy (DE-FG02-02ER63445

Production of 3D printed scale models from microscope volume datasets for use in STEM education

Understanding the three-dimensional morphology of a biological sample at the microscopic level is a prerequisite to a functional understanding of cell biology, tissue development and growth. Images of microscopic samples obtained by compound light microscopy are customarily recorded and represented in two dimensions from a single orientation making it difficult to extrapolate 3D context from the 2D information. The commercialisation of fast, laser-based microscope systems (e.g. confocal, multi-photon or lightsheet microscopy) capable of generating volume datasets of microscopic samples through optical sectioning, coupled with advances in computer technology allowing accurate volume rendering of these datasets, have facilitated significant improvement in our 3D understanding of the microscopic world in virtual space. The advent of affordable 3D printing technology now offers the prospect of generating morphologically accurate, physical models from these microscope volume datasets for use in science education, outreach and engagement. 3D printed scale replicas will provide improved sensory perception, offering tactile as well as visual interaction, leading to improved understanding of structure function relationships. Here we present a technique to reliably generate detailed, physical 3D models from Z-stacks of optical sections from confocal and lightsheet microscopes using affordable, entry-level 3D printing technology. We use the technique to generate 3D printed models of a variety of different biological samples at a range of scales including pollen grains from two species of plant; blood cells from both human and earthworm species, a section of plant root; the compound eye of an ant; and a developing Zebrafish larva; all of which have been used in our teaching, engagement and outreach activities. Our methods can, in principle, be used to generate 3D printed models from microscope volume datasets of any small fluorescent or reflective samples

Psychosocial and Quality of Life in Women Receiving the 21-Gene Recurrence Score Assay: The Impact of Decision Style in Women with Intermediate RS

Multigene assays such as the 21-gene recurrence score (RS) quantify risk for recurrence and potential benefit from chemotherapy in early-stage, ER+ breast cancers. Few studies have assessed the impact of testing on patient-reported outcomes such as cancer-related distress or quality of life. The few studies that have assessed these outcomes do not consider potential modifiers, such as the patients’ level of involvement in the treatment decision-making process. In the current study, 81 breast cancer patients who received the RS assay completed cross-sectional surveys. We used linear multiple regression to assess whether test result, decision-making role (passive versus shared/active), and their interaction contributed to current levels of distress, quality of life, and decisional conflict. There were no associations between these variables and test result or decision-making role. However, women who received an intermediate RS and took a passive role in their care reported higher-cancer-related distress and cancer worry and lower quality of life than those who took a shared or active role. These data should be confirmed in prospective samples, as these poorer outcomes could be amenable to intervention

Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2x)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted