AutoGater: a weakly supervised neural network model to gate cells in flow cytometric analyses.

Flow cytometry is a useful and efficient method for the rapid characterization of a cell population based on the optical and fluorescence properties of individual cells. Ideally, the cell population would consist of only healthy viable cells as dead cells can confound the analysis. Thus, separating out healthy cells from dying and dead cells, and any potential debris, is an important first step in analysis of flow cytometry data.

A yeast cell cycle pulse generator model shows consistency with multiple oscillatory and checkpoint mutant datasets.

Modeling biological systems holds great promise for speeding up the rate of discovery in systems biology by predicting experimental outcomes and suggesting targeted interventions. However, this process is dogged by an identifiability issue, in which network models and their parameters are not sufficiently constrained by coarse and noisy data to ensure unique solutions. In this work, we evaluated the capability of a simplified yeast cell-cycle network model to reproduce multiple observed transcriptomic behaviors under genomic mutations.

The parasite intraerythrocytic cycle and human circadian cycle are coupled during malaria infection.

During infections with the malaria parasites , patients exhibit rhythmic fevers every 48 h. These fever cycles correspond with the time the parasites take to traverse the intraerythrocytic cycle (IEC). In other species that infect either humans or mice, the IEC is likely guided by a parasite-intrinsic clock [Rijo-Ferreira, , 746-753 (2020); Smith .

Robustness and reproducibility of simple and complex synthetic logic circuit designs using a DBTL loop.

Computational tools addressing various components of design-build-test-learn (DBTL) loops for the construction of synthetic genetic networks exist but do not generally cover the entire DBTL loop. This manuscript introduces an end-to-end sequence of tools that together form a DBTL loop called Design Assemble Round Trip (DART). DART provides rational selection and refinement of genetic parts to construct and test a circuit.

Highly-automated, high-throughput replication of yeast-based logic circuit design assessments.

We describe an experimental campaign that replicated the performance assessment of logic gates engineered into cells of by Gander Our experimental campaign used a novel high-throughput experimentation framework developed under Defense Advanced Research Projects Agency's Synergistic Discovery and Design program: a remote robotic lab at Strateos executed a parameterized experimental protocol. Using this protocol and robotic execution, we generated two orders of magnitude more flow cytometry data than the original experiments. We discuss our results, which largely, but not completely, agree with the original report and make some remarks about lessons learned.

Experimental guidance for discovering genetic networks through hypothesis reduction on time series.

Large programs of dynamic gene expression, like cell cyles and circadian rhythms, are controlled by a relatively small "core" network of transcription factors and post-translational modifiers, working in concerted mutual regulation. Recent work suggests that system-independent, quantitative features of the dynamics of gene expression can be used to identify core regulators. We introduce an approach of iterative network hypothesis reduction from time-series data in which increasingly complex features of the dynamic expression of individual, pairs, and entire collections of genes are used to infer functional network models that can produce the observed transcriptional program.

Conservation of dynamic characteristics of transcriptional regulatory elements in periodic biological processes.

Background: Cell and circadian cycles control a large fraction of cell and organismal physiology by regulating large periodic transcriptional programs that encompass anywhere from 15 to 80% of the genome despite performing distinct functions. In each case, these large periodic transcriptional programs are controlled by gene regulatory networks (GRNs), and it has been shown through genetics and chromosome mapping approaches in model systems that at the core of these GRNs are small sets of genes that drive the transcript dynamics of the GRNs. However, it is unlikely that we have identified all of these core genes, even in model organisms.

Round Trip: An Automated Pipeline for Experimental Design, Execution, and Analysis.

Synthetic biology is a complex discipline that involves creating detailed, purpose-built designs from genetic parts. This process is often phrased as a Design-Build-Test-Learn loop, where iterative design improvements can be made, implemented, measured, and analyzed. Automation can potentially improve both the end-to-end duration of the process and the utility of data produced by the process.

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline.

Developing gene regulatory network models is a major challenge in systems biology. Several computational tools and pipelines have been developed to tackle this challenge, including the newly developed Inherent Dynamics Pipeline. The Inherent Dynamics Pipeline consists of several previously published tools that work synergistically and are connected in a linear fashion, where the output of one tool is then used as input for the following tool.

Impact of Sickle Cell Trait Hemoglobin on the Intraerythrocytic Transcriptional Program of Plasmodium falciparum.

Sickle-trait hemoglobin (HbAS) confers nearly complete protection from severe, life-threatening falciparum malaria in African children. Despite this clear protection, the molecular mechanisms by which HbAS confers these protective phenotypes remain incompletely understood. As a forward genetic screen for aberrant parasite transcriptional responses associated with parasite neutralization in HbAS red blood cells (RBCs), we performed comparative transcriptomic analyses of Plasmodium falciparum in normal (HbAA) and HbAS erythrocytes during both cultivation of reference parasite strains and naturally occurring P.

Inference of Gene Regulatory Network Uncovers the Linkage between Circadian Clock and Crassulacean Acid Metabolism in .

The circadian clock drives time-specific gene expression, enabling biological processes to be temporally controlled. Plants that conduct crassulacean acid metabolism (CAM) photosynthesis represent an interesting case of circadian regulation of gene expression as stomatal movement is temporally inverted relative to stomatal movement in C3 plants. The mechanisms behind how the circadian clock enabled physiological differences at the molecular level is not well understood.

Comparative Genomics Analysis Provides New Insight Into Molecular Basis of Stomatal Movement in .

CO uptake and water loss in plants are regulated by microscopic pores on the surface of leaves, called stomata. This enablement of gas exchange by the opening and closing of stomata is one of the most essential processes in plant photosynthesis and transpiration, affecting water-use efficiency (WUE) and thus drought susceptibility. In plant species with crassulacean acid metabolism (CAM) photosynthesis, diel stomatal movement pattern is inverted relative to C and C photosynthesis species, resulting in much higher WUE and drought tolerance.

Conservation and Diversification of Circadian Rhythmicity Between a Model Crassulacean Acid Metabolism Plant and a Model C Photosynthesis Plant .

Crassulacean acid metabolism (CAM) improves photosynthetic efficiency under limited water availability relative to C photosynthesis. It is widely accepted that CAM plants have evolved from C plants and it is hypothesized that CAM is under the control of the internal circadian clock. However, the role that the circadian clock plays in the evolution of CAM is not well understood.

Perspectives on the basic and applied aspects of crassulacean acid metabolism (CAM) research.

Due to public concerns about the decreasing supply of blue water and increasing heat and drought stress on plant growth caused by urbanization, increasing human population and climate change, interest in crassulacean acid metabolism (CAM), a specialized type of photosynthesis enhancing water-use efficiency (WUE) and drought tolerance, has increased markedly. Significant progress has been achieved in both basic and applied research in CAM plants since the beginning of this century. Here we provide a brief overview of the current status of CAM research, and discuss future needs and opportunities in a wide range of areas including systems biology, synthetic biology, and utilization of CAM crops for human benefit, with a focus on the following aspects: 1) application of genome-editing technology and high-throughput phenotyping to functional genomics research in model CAM species and genetic improvement of CAM crops, 2) challenges for multi-scale metabolic modeling of CAM systems, 3) opportunities and new strategies for CAM pathway engineering to enhance WUE and drought tolerance in C (and C) photosynthesis crops, 4) potential of CAM species as resources for food, feed, natural products, pharmaceuticals and biofuels, and 5) development of CAM crops for ecological and aesthetic benefits.

The Kalanchoë genome provides insights into convergent evolution and building blocks of crassulacean acid metabolism.

Crassulacean acid metabolism (CAM) is a water-use efficient adaptation of photosynthesis that has evolved independently many times in diverse lineages of flowering plants. We hypothesize that convergent evolution of protein sequence and temporal gene expression underpins the independent emergences of CAM from C photosynthesis. To test this hypothesis, we generate a de novo genome assembly and genome-wide transcript expression data for Kalanchoë fedtschenkoi, an obligate CAM species within the core eudicots with a relatively small genome (~260 Mb).

Sudden early-morning awakening impairs immediate tactical planning in a changing 'emergency' scenario.

This was a realistic military-type exercise assessing unexpected, abrupt early-morning awakening effects on immediate 'executive function' and the ability to comprehend and deal with a sudden emergency under a changing situation. Twenty (average age 21years) healthy, highly motivated junior officer reservists were assigned randomly to two equal, independent groups, unforewarned as to what would happen. The experimental group was woken abruptly at 03:00h (<3h sleep) and confronted immediately with a 'paper exercise' of an enemy attack, requiring a feasible plan of engagement with minimal loss of resources, to be completed within 15min.

Bayesian belief network for the Gleason patterns in prostatic adenocarcinoma: development of a diagnostic decision support system for educational purposes.

Objective: To develop a Bayesian belief network (BBN) for Gleason grading of prostate adenocarcinoma.

Study Design: A shallow network was developed for Gleason grading with open-tree topology, with a root node containing 5 subjective diagnostic alternatives and 8 first-level descendant nodes for diagnostic features. Features or diagnostic clues of the descendant nodes were based on architecture of Gleason patterns.