GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.

Download Full-text

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown roots systems

10.1101/016931 ◽

2015 ◽

Cited By ~ 3

Author(s):

Rubén Rellán-Álvarez ◽

Guillaume Lobet ◽

Heike Lindner ◽

Pierre-Luc M Pradier ◽

Jose Sebastian ◽

...

Keyword(s):

Imaging System ◽

Expression Patterns ◽

Root Traits ◽

Local Environment ◽

Spatial Integration ◽

Adaptive Responses ◽

Physiological Relevance ◽

Great Utility ◽

Systemic Signals

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties such as soil moisture with root traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.

Download Full-text

Conserved and muscle-group-specific gene expression patterns shape postnatal development of the novel extraocular muscle phenotype

Physiological Genomics ◽

10.1152/physiolgenomics.00222.2003 ◽

2004 ◽

Vol 18 (2) ◽

pp. 184-195 ◽

Cited By ~ 22

Author(s):

Georgiana Cheng ◽

Anita P. Merriam ◽

Bendi Gong ◽

Patrick Leahy ◽

Sangeeta Khanna ◽

...

Keyword(s):

Gene Expression ◽

Skeletal Muscle ◽

System Development ◽

Expression Patterns ◽

Neuromuscular Diseases ◽

Local Environment ◽

Oculomotor System ◽

Muscle Group ◽

Specific Gene ◽

Extrinsic Factors

Current models in skeletal muscle biology do not fully account for the breadth, causes, and consequences of phenotypic variation among skeletal muscle groups. The muscle allotype concept arose to explain frank differences between limb, masticatory, and extraocular (EOM) muscles, but there is little understanding of the developmental regulation of the skeletal muscle phenotypic range. Here, we used morphological and DNA microarray analyses to generate a comprehensive temporal profile for rat EOM development. Based upon coordinate regulation of morphologic/gene expression traits with key events in visual, vestibular, and oculomotor system development, we propose a model that the EOM phenotype is a consequence of extrinsic factors that are unique to its local environment and sensory-motor control system, acting upon a novel myoblast lineage. We identified a broad spectrum of differences between the postnatal transcriptional patterns of EOM and limb muscle allotypes, including numerous transcripts not traditionally associated with muscle fiber/group differences. Several transcription factors were differentially regulated and may be responsible for signaling muscle allotype specificity. Significant differences in cellular energetic mechanisms defined the EOM and limb allotypes. The allotypes were divergent in many other functional transcript classes that remain to be further explored. Taken together, we suggest that the EOM allotype is the consequence of tissue-specific mechanisms that direct expression of a limited number of EOM-specific transcripts and broader, incremental differences in transcripts that are conserved by the two allotypes. This represents an important first step in dissecting allotype-specific regulatory mechanisms that may, in turn, explain differential muscle group sensitivity to a variety of metabolic and neuromuscular diseases.

Download Full-text

Transcriptome and Proteome Analysis of Bacillus subtilis Gene Expression Modulated by Amino Acid Availability

Journal of Bacteriology ◽

10.1128/jb.184.15.4288-4295.2002 ◽

2002 ◽

Vol 184 (15) ◽

pp. 4288-4295 ◽

Cited By ~ 45

Author(s):

Ulrike Mäder ◽

Georg Homuth ◽

Christian Scharf ◽

Knut Büttner ◽

Rüdiger Bode ◽

...

Keyword(s):

Gene Expression ◽

Bacillus Subtilis ◽

Amino Acid ◽

Expression Patterns ◽

Proteome Analysis ◽

Protein Gel ◽

Amino Acid Availability ◽

Physiological Relevance ◽

Casamino Acids

ABSTRACT A comprehensive study of Bacillus subtilis gene expression patterns in response to amino acid availability was performed by means of proteomics and transcriptomics. The methods of two-dimensional protein gel electrophoresis and DNA macroarray technology were combined to analyze cells exponentially grown in minimal medium with and without 0.2% Casamino Acids (CAA). This approach revealed about 120 genes predominantly involved in amino acid biosynthesis, sporulation, and competence, which were downregulated in CAA-containing medium. Determination of sporulation frequencies confirmed the physiological relevance of the expression data.

Download Full-text

Engineered phenotype patterns in microbial populations

10.1101/575068 ◽

2019 ◽

Author(s):

Philip Bittihn ◽

Andriy Didovyk ◽

Lev S. Tsimring ◽

Jeff Hasty

Keyword(s):

Gene Expression ◽

Synthetic Biology ◽

Expression Patterns ◽

Local Environment ◽

Heterogeneous Environments ◽

Gene Circuits ◽

Sensor Module ◽

Dividing Cells ◽

Actuator Module ◽

And Control

AbstractRapid advances in cellular engineering1,2have positioned synthetic biology to address therapeutic3,4and industrial5problems, but a significant obstacle is the myriad of unanticipated cellular responses in heterogeneous environments such as the gut6,7, solid tumors8,9, bioreactors10or soil11. Complex interactions between the environment and cells often arise through non-uniform nutrient availability, which can generatebidirectionalcoupling as cells both adjust to and modify their local environment through different growth phenotypes across a colony.12,13While spatial sensing14and gene expression patterns15–17have been explored under homogeneous conditions, the mutual interaction between gene circuits, growth phenotype, and the environment remains a challenge for synthetic biology. Here, we design gene circuits which sense and control spatiotemporal phenotype patterns in a model system of heterogeneous microcolonies containing both growing and dormant bacteria. We implement pattern control by coupling different downstream modules to a tunable sensor module that leveragesE. coli⁉sstress response and is activated upon growth arrest. One is an actuator module that slows growth and thereby creates an environmental negative feedback via nutrient diffusion. We build a computational model of this system to understand the interplay between gene regulation, population dynamics, and chemical transport, which predicts oscillations in both growth and gene expression. Experimentally, this circuit indeed generates robust cycling between growth and dormancy in the interior of the colony. We also use the stress sensor to drive an inducible gating module that enables selective gene expression in non-dividing cells. The ‘stress-gated lysis circuit’ derived from this module radically alters the growth pattern through elimination of the dormant phenotype upon a chemical cue. Our results establish a strategy to leverage and control the presence of distinct microbial growth phenotypes for synthetic biology applications in complex environments.

Download Full-text

A multiscale model of complex endothelial cell dynamics in early angiogenesis

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008055 ◽

2021 ◽

Vol 17 (1) ◽

pp. e1008055

Author(s):

Daria Stepanova ◽

Helen M. Byrne ◽

Philip K. Maini ◽

Tomás Alarcón

Keyword(s):

Gene Expression ◽

Expression Patterns ◽

Experimental Studies ◽

Notch Pathway ◽

Local Environment ◽

Multiscale Model ◽

Vascular Network ◽

Border Effect ◽

Potential Biomarker ◽

The Impact

We introduce a hybrid two-dimensional multiscale model of angiogenesis, the process by which endothelial cells (ECs) migrate from a pre-existing vascular bed in response to local environmental cues and cell-cell interactions, to create a new vascular network. Recent experimental studies have highlighted a central role of cell rearrangements in the formation of angiogenic networks. Our model accounts for this phenomenon via the heterogeneous response of ECs to their microenvironment. These cell rearrangements, in turn, dynamically remodel the local environment. The model reproduces characteristic features of angiogenic sprouting that include branching, chemotactic sensitivity, the brush border effect, and cell mixing. These properties, rather than being hardwired into the model, emerge naturally from the gene expression patterns of individual cells. After calibrating and validating our model against experimental data, we use it to predict how the structure of the vascular network changes as the baseline gene expression levels of the VEGF-Delta-Notch pathway, and the composition of the extracellular environment, vary. In order to investigate the impact of cell rearrangements on the vascular network structure, we introduce the mixing measure, a scalar metric that quantifies cell mixing as the vascular network grows. We calculate the mixing measure for the simulated vascular networks generated by ECs of different lineages (wild type cells and mutant cells with impaired expression of a specific receptor). Our results show that the time evolution of the mixing measure is directly correlated to the generic features of the vascular branching pattern, thus, supporting the hypothesis that cell rearrangements play an essential role in sprouting angiogenesis. Furthermore, we predict that lower cell rearrangement leads to an imbalance between branching and sprout elongation. Since the computation of this statistic requires only individual cell trajectories, it can be computed for networks generated in biological experiments, making it a potential biomarker for pathological angiogenesis.

Download Full-text

Affordable and robust phenotyping framework to analyse root system architecture of soil-grown plants

10.1101/573139 ◽

2019 ◽

Cited By ~ 1

Author(s):

Thibaut Bontpart ◽

Cristobal Concha ◽

Valerio Giuffrida ◽

Ingrid Robertson ◽

Kassahun Admkie ◽

...

Keyword(s):

Root System ◽

Low Income ◽

System Architecture ◽

Imaging System ◽

Soil Surface ◽

Root Systems ◽

Root System Architecture ◽

Low Income Countries ◽

Climate Resilience ◽

Root Phenotyping

AbstractThe analysis of root system growth, root phenotyping, is important to inform efforts to enhance plant resource acquisition from soils. However, root phenotyping remains challenging due to soil opacity and requires systems that optimize root visibility and image acquisition. Previously reported systems require costly and bespoke materials not available in most countries, where breeders need tools to select varieties best adapted to local soils and field conditions. Here, we present an affordable soil-based growth container (rhizobox) and imaging system to phenotype root development in greenhouses or shelters. All components of the system are made from commodity components, locally available worldwide to facilitate the adoption of this affordable technology in low-income countries. The rhizobox is large enough (~6000 cm2 visible soil) to not restrict vertical root system growth for at least seven weeks after sowing, yet light enough (~21 kg) to be routinely moved manually. Support structures and an imaging station, with five cameras covering the whole soil surface, complement the rhizoboxes. Images are acquired via the Phenotiki sensor interface, collected, stitched and analysed. Root system architecture (RSA) parameters are quantified without intervention. RSA of a dicot (chickpea, Cicer arietinum L.) and a monocot (barley, Hordeum vulgare L.) species, which exhibit contrasting root systems, were analysed. The affordable system is relevant for efforts in Ethiopia and elsewhere to enhance yields and climate resilience of chickpea and other crops for improved food security.Significance StatementAn affordable system to characterize root system architecture of soil-grown plants was developed. Using commodity components, this will enable local efforts world-wide to breed for enhanced root systems.

Download Full-text