Biological Systems from an Engineer’s Point of View

Mathematical modeling of the processes that pattern embryonic development (often called biological pattern formation) has a long and rich history [1,2]. These models proposed sets of hypothetical interactions, which, upon analysis, were shown to be capable of generating patterns reminiscent of those seen in the biological world, such as stripes, spots, or graded properties. Pattern formation models typically demonstrated the sufficiency of given classes of mechanisms to create patterns that mimicked a particular biological pattern or interaction. In the best cases, the models were able to make testable predictions [3], permitting them to be experimentally challenged, to be revised, and to stimulate yet more experimental tests (see review in [4]). In many other cases, however, the impact of the modeling efforts was mitigated by limitations in computer power and biochemical data. In addition, perhaps the most limiting factor was the mindset of many modelers, using Occam’s razor arguments to make the proposed models as simple as possible, which often generated intriguing patterns, but those patterns lacked the robustness exhibited by the biological system. In hindsight, one could argue that a greater attention to engineering principles would have focused attention on these shortcomings, including potential failure modes, and would have led to more complex, but more robust, models. Thus, despite a few successful cases in which modeling and experimentation worked in concert, modeling fell out of vogue as a means to motivate decisive test experiments. The recent explosion of molecular genetic, genomic, and proteomic data—as well as of quantitative imaging studies of biological tissues—has changed matters dramatically, replacing a previous dearth of molecular details with a wealth of data that are difficult to fully comprehend. This flood of new data has been accompanied by a new influx of physical scientists into biology, including engineers, physicists, and applied mathematicians [5–7]. These individuals bring with them the mindset, methodologies, and mathematical toolboxes common to their own fields, which are proving to be appropriate for analysis of biological systems. However, due to inherent complexity, biological systems seem to be like nothing previously encountered in the physical sciences. Thus, biological systems offer cutting edge problems for most scientific and engineering-related disciplines. It is therefore no wonder that there might seem to be a “bandwagon” of new biology-related research programs in departments that have traditionally focused on nonliving systems. Modeling biological interactions as dynamical systems (i.e., systems of variables changing in time) allows investigation of systems-level topics such as the robustness of patterning mechanisms, the role of feedback, and the self-regulation of size. The use of tools from engineering and applied mathematics, such as sensitivity analysis and control theory, is becoming more commonplace in biology. In addition to giving biologists some new terminology for describing their systems, such analyses are extremely useful in pointing to missing data and in testing the validity of a proposed mechanism. A paper in this issue of PLoS Biology clearly and honestly applies analytical tools to the authors’ research and obtains insights that would have been difficult if not impossible by other means [8]

Constructing the bundle sheath towards enhanced photosynthesis.

This article comments on: van Rooijen R, Schulze S, Petzsch P, Westhoff P. 2020. Targeted misexpression of NAC052, acting in H3K4 demethylation, alters leaf morphological and anatomical traits in Arabidopsis thaliana. Journal of Experimental Botany 71, 1434–1448

Graded Dorsal and Differential Gene Regulation in the Drosophila Embryo

A gradient of Dorsal activity patterns the dorsoventral (DV) axis of the early Drosophila melanogaster embryo by controlling the expression of genes that delineate presumptive mesoderm, neuroectoderm, and dorsal ectoderm. The availability of the Drosophila melanogaster genome sequence has accelerated the study of embryonic DV patterning, enabling the use of systems-level approaches. As a result, our understanding of Dorsal-dependent gene regulation has expanded to encompass a collection of more than 50 genes and 30 cis-regulatory sequences. This information, which has been integrated into a spatiotemporal atlas of gene regulatory interactions, comprises one of the best-understood networks controlling any developmental process to date. In this article, we focus on how Dorsal controls differential gene expression and how recent studies have expanded our understanding of Drosophila embryonic development from the cis-regulatory level to that controlling morphogenesis of the embryo

Size-dependent regulation of dorsal–ventral patterning in the early Drosophila embryo

How natural variation in embryo size affects patterning of the Drosophila embryo dorsal–ventral (DV) axis is not known. Here we examined quantitatively the relationship between nuclear distribution of the Dorsal transcription factor, boundary positions for several target genes, and DV axis length. Data were obtained from embryos of a wild-type background as well as from mutant lines inbred to size select embryos of smaller or larger sizes. Our data show that the width of the nuclear Dorsal gradient correlates with DV axis length. In turn, for some genes expressed along the DV axis, the boundary positions correlate closely with nuclear Dorsal levels and with DV axis length; while the expression pattern of others is relatively constant and independent of the width of the Dorsal gradient. In particular, the patterns of snail (sna) and ventral nervous system defective (vnd) correlate with nuclear Dorsal levels and exhibit scaling to DV length; while the pattern of intermediate neuroblasts defective (ind) remains relatively constant with respect to changes in Dorsal and DV length. However, in mutants that exhibit an abnormal expansion of the Dorsal gradient which fails to scale to DV length, only sna follows the Dorsal distribution and exhibits overexpansion; in contrast, vnd and ind do not overexpand suggesting some additional mechanism acts to refine the dorsal boundaries of these two genes. Thus, our results argue against the idea that the Dorsal gradient works as a global system of relative coordinates along the DV axis and suggest that individual targets respond to changes in embryo size in a gene-specific manner

Image analysis and empirical modeling of gene and protein expression

Protein gradients and gene expression patterns are major determinants in the differentiation and fate map of the developing embryo. Here we discuss computational methods to quantitatively measure the positions of gene expression domains and the gradients of protein expression along the dorsal–ventral axis in the Drosophila embryo. Our methodology involves three layers of data. The first layer, or the primary data, consists of z-stack confocal images of embryos processed by in situ hybridization and/or antibody stainings. The secondary data are relationships between location, usually an x-axis coordinate, and fluorescent intensity of gene or protein detection. Tertiary data comprise the optimal parameters that arise from fits of the secondary data to empirical models. The tertiary data are useful to distill large datasets of imaged embryos down to a tractable number of conceptually useful parameters. This analysis allows us to detect subtle phenotypes and is adaptable to any set of genes or proteins with a canonical pattern. For example, we show how insights into the Dorsal transcription factor protein gradient and its target gene ventral-neuroblasts defective (vnd) were obtained using such quantitative approaches

Successful Desensitization to Docetaxel after Severe Hypersensitivity Reactions in Two Patients

Purpose Two cases of successful desensitization to docetaxel after severe hypersensitivity reactions are reported. Summary Two patients with gynecological malignancies (uterine leiomyosarcoma and ovarian adenocarcinoma) experienced severe hypersensitivity reactions with docetaxel, including flushing, numbness, sharp radiating pain, severe nausea and vomiting, apnea, and unresponsiveness. Both patients received ondansetron before docetaxel. One patient received dexamethasone, diphenhydramine, and famotidine premedication before docetaxel, as she had previously reacted to paclitaxel. Docetaxel infusions were stopped, and the reactions were treated with diphenhydramine and dexamethasone (one patient also received famotidine). After resolution of symptoms, the docetaxel was not reinitiated due to the nature of the reactions. For the next cycle, both patients received a graded drug challenge or desensitization. Both were pre-medicated with dexamethasone, diphenhydramine, and famotidine. The docetaxel was given as infusions of 0.1%, 1%, and 10% of the dose, with each infusion given over one hour. After this, the remainder of the dose was infused over one hour. Both patients tolerated this desensitization well and completed a total of three and four cycles each. The first patient to receive the desensitization did complain of chest pain during the first desensitization, and the infusion rate was decreased to administer the drug over two hours. After she tolerated two cycles of two-hour infusions, the infusion rate was increased to administer each docetaxel infusion over one hour. Conclusion Two patients who had severe hypersensitivity reactions to docetaxel successfully received further docetaxel doses via a desensitization procedure that involved the sequential administration of solutions containing increasing concentrations of the drug

NUMERICAL ANALYSIS OF A COMPOSITE STEEL BOX GIRDER BRIDGE IN FIRE

Box girder bridges are becoming more common because of their ease of construction, pleasing appearance, and serviceability. Projects with curved configuration and long spans can especially benefit from these advantages. However, the industry lacks a wide range of research on multi-span steel box girder cross-sections and their response to fire events. This poses a major risk to unprotected steel bridges using a box girder design. This paper will discuss a mathematical approach to determining and classifying different failure modes of weathering steel box girder bridges subject to two fire cases. Due to the rapid increase of temperature in the thin steel members, the strength of the steel deteriorates quickly. Results show that different fire locations can greatly affect the forces that act on the individual members of the structure

Regulatory gateways for cell-specific gene expression in C4 leaves with Kranz anatomy.

C4 photosynthesis is a carbon-concentrating mechanism that increases delivery of carbon dioxide to RuBisCO and as a consequence reduces photorespiration. The C4 pathway is therefore beneficial in environments that promote high photorespiration. This pathway has evolved many times, and involves restricting gene expression to either mesophyll or bundle sheath cells. Here we review the regulatory mechanisms that control cell-preferential expression of genes in the C4 cycle. From this analysis, it is clear that the C4 pathway has a complex regulatory framework, with control operating at epigenetic, transcriptional, post-transcriptional, translational, and post-translational levels. Some genes of the C4 pathway are regulated at multiple levels, and we propose that this ensures robust expression in each cell type. Accumulating evidence suggests that multiple genes of the C4 pathway may share the same regulatory mechanism. The control systems for C4 photosynthesis gene expression appear to operate in C3 plants, and so it appears that pre-existing mechanisms form the basis of C4 photosynthesis gene expression

Structure and functional motifs of GCR1, the only plant protein with a GPCR fold?

Whether GPCRs exist in plants is a fundamental biological question. Interest in deorphanizing new G protein coupled receptors (GPCRs), arises because of their importance in signaling. Within plants, this is controversial as genome analysis has identified 56 putative GPCRs, including GCR1 which is reportedly a remote homologue to class A, B and E GPCRs. Of these, GCR2, is not a GPCR; more recently it has been proposed that none are, not even GCR1. We have addressed this disparity between genome analysis and biological evidence through a structural bioinformatics study, involving fold recognition methods, from which only GCR1 emerges as a strong candidate. To further probe GCR1, we have developed a novel helix alignment method, which has been benchmarked against the the class A – class B - class F GPCR alignments. In addition, we have presented a mutually consistent set of alignments of GCR1 homologues to class A, class B and class F GPCRs, and shown that GCR1 is closer to class A and /or class B GPCRs than class A, class B or class F GPCRs are to each other. To further probe GCR1, we have aligned transmembrane helix 3 of GCR1 to each of the 6 GPCR classes. Variability comparisons provide additional evidence that GCR1 homologues have the GPCR fold. From the alignments and a GCR1 comparative model we have identified motifs that are common to GCR1, class A, B and E GPCRs. We discuss the possibilities that emerge from this controversial evidence that GCR1 has a GPCR fol