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1. Effective drug combination for Caenorhabditis elegans nematodes discovered by output-driven feedback system control technique

   https://doi.org/10.1126/sciadv.aao1254  

   Ding, Xianting; Njus, Zach; Kong, Taejoon; Su, Wenqiong; Ho, Chih-Ming; Pandey, Santosh (October 2017, Science Advances)

   Infections from parasitic nematodes (or roundworms) contribute to a significant disease burden and productivity losses for humans and livestock. The limited number of anthelmintics (or antinematode drugs) available today to treat these infections are rapidly losing their efficacy as multidrug resistance in parasites becomes a global health challenge. We propose an engineering approach to discover an anthelmintic drug combination that is more potent at killing wild-type Caenorhabditis elegans worms than four individual drugs. In the experiment, freely swimming single worms are enclosed in microfluidic drug environments to assess the centroid velocity and track curvature of worm movements. After analyzing the behavioral data in every iteration, the feedback system control (FSC) scheme is used to predict new drug combinations to test. Through a differential evolutionary search, the winning drug combination is reached that produces minimal centroid velocity and high track curvature, while requiring each drug in less than their EC 50 concentrations. The FSC approach is model-less and does not need any information on the drug pharmacology, signaling pathways, or animal biology. Toward combating multidrug resistance, the method presented here is applicable to the discovery of new potent combinations of available anthelmintics on C. elegans , parasitic nematodes, and other small model organisms. 

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2. Editorial: Model organisms in plant developmental biology—their effectiveness and limitations

   https://doi.org/10.3389/fpls.2024.1478483  

   Di_Stilio, Verónica S; Sinha, Neelima R (September 2024, Frontiers in Plant Science)

   Cheng, Chi-Lien (Ed.)

   Model organisms represent an invaluable resource for fundamental and applied research allowing the identification of the mechanistic basis of evolutionary innovations. This Research Topic showcases studies performed on established and emerging model organisms in Plant Developmental Biology that have broad significance to the field. Increased phylogenetic breadth and availability of genomes and transgenic techniques have fostered innovative ideas and syntheses spanning the range from fossil analyses to single-cell sequencing. However, broad taxonomic applicability of the knowledge gained from studies on model organisms and relevance to the field of Evolutionary Developmental Biology (Evo-Devo) often remains unresolved. To address such questions, this Research Topic focuses on new insights, latest discoveries, current challenges, and future perspectives on the use of model organisms and the extent to which the knowledge gained from them can be extrapolated. Authors were encouraged to identify the greatest unifying concepts in their sub-disciplines, as well as to put forward potential solutions to address the challenges emerging from the use of model plants. 

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3. Time-Based Systems Biology Approaches to Capture and Model Dynamic Gene Regulatory Networks

   https://doi.org/10.1146/annurev-arplant-081320-090914  

   Alvarez, Jose M.; Brooks, Matthew D.; Swift, Joseph; Coruzzi, Gloria M. (May 2021, Annual Review of Plant Biology)

   null (Ed.)

   All aspects of transcription and its regulation involve dynamic events. However, capturing these dynamic events in gene regulatory networks (GRNs) offers both a promise and a challenge. The promise is that capturing and modeling the dynamic changes in GRNs will allow us to understand how organisms adapt to a changing environment. The ability to mount a rapid transcriptional response to environmental changes is especially important in nonmotile organisms such as plants. The challenge is to capture these dynamic, genome-wide events and model them in GRNs. In this review, we cover recent progress in capturing dynamic interactions of transcription factors with their targets—at both the local and genome-wide levels—and using them to learn how GRNs operate as a function of time. We also discuss recent advances that employ time-based machine learning approaches to forecast gene expression at future time points, a key goal of systems biology. Expected final online publication date for the Annual Review of Plant Biology, Volume 72 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

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4. Tardigrades and their emergence as model organisms

   https://doi.org/https://doi.org/10.1016/bs.ctdb.2021.12.008  

   Goldstein, Bob (January 2022, Current topics in developmental biology)

   Goldstein, Bob; Srivastava, Mansi (Ed.)

   Experimentally tractable organisms like C. elegans, Drosophila, zebrafish, and mouse are popular models for addressing diverse questions in biology. In 1997, two of the most valuable invertebrate model organisms to date—C. elegans and Drosophila—were found to be much more closely related to each other than expected. C. elegans and Drosophila belong to the nematodes and arthropods, respectively, and these two phyla and six other phyla make up a clade of molting animals referred to as the Ecdysozoa. The other ecdysozoan phyla could be valuable models for comparative biology, taking advantage of the rich and continual sources of research findings as well as tools from both C. elegans and Drosophila. But when the Ecdysozoa was first recognized, few tools were available for laboratory studies in any of these six other ecdysozoan phyla. In 1999 I began an effort to develop tools for studying one such phylum, the tardigrades. Here, I describe how the tardigrade species Hypsibius exemplaris and tardigrades more generally have emerged over the past two decades as valuable new models for answering diverse questions. To date, these questions have included how animal body plans evolve and how biological materials can survive some remarkably extreme conditions. 

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5. Microfluidic techniques for isolation, formation, and characterization of circulating tumor cells and clusters

   https://doi.org/10.1063/5.0093806  

   Macaraniag, Celine; Luan, Qiyue; Zhou, Jian; Papautsky, Ian (September 2022, APL Bioengineering)

   Circulating tumor cell (CTC) clusters that are shed from the primary tumor into the bloodstream are associated with a poor prognosis, elevated metastatic potential, higher proliferation rate, and distinct molecular features compared to single CTCs. Studying CTC clusters may give us information on the differences in the genetic profiles, somatic mutations, and epigenetic changes in circulating cells compared to the primary tumor and metastatic sites. Microfluidic systems offer the means of studying CTC clusters through the ability to efficiently isolate these rare cells from the whole blood of patients in a liquid biopsy. Microfluidics can also be used to develop in vitro models of CTC clusters and make possible their characterization and analysis. Ultimately, microfluidic systems can offer the means to gather insight on the complexities of the metastatic process, the biology of cancer, and the potential for developing novel or personalized therapies. In this review, we aim to discuss the advantages and challenges of the existing microfluidic systems for working with CTC clusters. We hope that an improved understanding of the role microfluidics can play in isolation, formation, and characterization of CTC clusters, which can lead to increased sophistication of microfluidic platforms in cancer research. 

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