Alexandre Cunha

Fast nonlocal filtering applied to electron cryomicroscopy

We present an efficient algorithm for nonlocal image filtering with applications in electron cryomicroscopy. Our denoising algorithm is a rewriting of the recently proposed nonlocal mean filter. It builds on the separable property of neighborhood filtering to offer a fast parallel and vectorized implementation in contemporary shared memory computer architectures while reducing the theoretical computational complexity of the original filter. In practice, our approach is much faster than a serial, non-vectorized implementation and it scales linearly with image size. We demonstrate its efficiency in data sets from Caulobacter crescentus tomograms and a cryoimage containing viruses and provide visual evidences attesting the remarkable quality of the nonlocal means scheme in the context of cryoimaging. With such development we provide biologists with an attractive filtering tool to facilitate their scientific discoveries.

Computational morphodynamics of plants: integrating development over space and time

The emerging field of computational morphodynamics aims to understand the changes that occur in space and time during development by combining three technical strategies: live imaging to observe development as it happens; image processing and analysis to extract quantitative information; and computational modelling to express and test time-dependent hypotheses. The strength of the field comes from the iterative and combined use of these techniques, which has provided important insights into plant development.

Computational Morphodynamics: A Modeling Framework to Understand Plant Growth

Computational morphodynamics utilizes computer modeling to understand the development of living organisms over space and time. Results from biological experiments are used to construct accurate and predictive models of growth. These models are then used to make novel predictions that provide further insight into the processes involved, which can be tested experimentally to either confirm or rule out the validity of the computational models. This review highlights two fundamental challenges: (a) to understand the feedback between mechanics of growth and chemical or molecular signaling, and (b) to design models that span and integrate single cell behavior with tissue development. We review different approaches to model plant growth and discuss a variety of model types that can be implemented to demonstrate how the interplay between computational modeling and experimentation can be used to explore the morphodynamics of plant development.

Auxin depletion from leaf primordia contributes to organ patterning

Significance Stem cells not only initiate organs, but may also contribute to organ patterning, at least in the shoot apex of flowering plants: classical microsurgical experiments imply that the shoot apical meristem promotes development of the leaf adaxial side, i.e., the upper side. In this study, we show the existence of a transient low auxin zone in the adaxial side that contributes to adaxial development. We further find that this adaxial low auxin zone results from auxin transport from leaves to the shoot apex. Thus, it is not a positive signal from stem cells, but departure of a signaling molecule from primordia to stem cells, that delivers polarity information—opposite to what is generally assumed. Stem cells are responsible for organogenesis, but it is largely unknown whether and how information from stem cells acts to direct organ patterning after organ primordia are formed. It has long been proposed that the stem cells at the plant shoot apex produce a signal, which promotes leaf adaxial-abaxial (dorsoventral) patterning. Here we show the existence of a transient low auxin zone in the adaxial domain of early leaf primordia. We also demonstrate that this adaxial low auxin domain contributes to leaf adaxial-abaxial patterning. The auxin signal is mediated by the auxin-responsive transcription factor MONOPTEROS (MP), whose constitutive activation in the adaxial domain promotes abaxial cell fate. Furthermore, we show that auxin flow from emerging leaf primordia to the shoot apical meristem establishes the low auxin zone, and that this auxin flow contributes to leaf polarity. Our results provide an explanation for the hypothetical meristem-derived leaf polarity signal. Opposite to the original proposal, instead of a signal derived from the meristem, we show that a signaling molecule is departing from the primordium to the meristem to promote robustness in leaf patterning.

A computational image analysis glossary for biologists

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

Segmenting the sepal and shoot apical meristem of Arabidopsis thaliana

We present methods for segmenting the sepal and shoot apical meristem of the Arabidopsis thaliana plant. We propose a mathematical morphology pipeline and a modified numerical scheme for the active contours without edges algorithm to extract the geometry and topology of plant cells imaged using confocal laser scanning microscopy. We demonstrate our methods in typical images used in the studies of cell endoreduplication and hormone transport and show that in practice they produce highly accurate results requiring little human intervention to cope with image aberrations.

IRMA: An Image Registration Meta-algorithm

IRMA is a meta-algorithmfor image registration (image alignment), evaluating results under multiple metrics using the LONI Pipeline workflow infrastructure, on the LONI/CCB grid computing facility. IRMA manages these results in a model base implemented with PostgreSQL. It permits scientists to catalog the results such as provenance information, and permits subsequent mining -- exploring the space of alternatives in an organized fashion and building understanding about individual algorithms, and learn about strengths and weaknesses of algorithms over time.

Third-generation in situ hybridization chain reaction: Multiplexed, quantitative, sensitive, versatile, robust

ABSTRACT In situ hybridization based on the mechanism of the hybridization chain reaction (HCR) has addressed multi-decade challenges that impeded imaging of mRNA expression in diverse organisms, offering a unique combination of multiplexing, quantitation, sensitivity, resolution and versatility. Here, with third-generation in situ HCR, we augment these capabilities using probes and amplifiers that combine to provide automatic background suppression throughout the protocol, ensuring that reagents will not generate amplified background even if they bind non-specifically within the sample. Automatic background suppression dramatically enhances performance and robustness, combining the benefits of a higher signal-to-background ratio with the convenience of using unoptimized probe sets for new targets and organisms. In situ HCR v3.0 enables three multiplexed quantitative analysis modes: (1) qHCR imaging – analog mRNA relative quantitation with subcellular resolution in the anatomical context of whole-mount vertebrate embryos; (2) qHCR flow cytometry – analog mRNA relative quantitation for high-throughput expression profiling of mammalian and bacterial cells; and (3) dHCR imaging – digital mRNA absolute quantitation via single-molecule imaging in thick autofluorescent samples. Highlighted Article: In situ hybridization chain reaction (HCR) v3.0 exploits automatic background suppression to enable multiplexed quantitative mRNA imaging and flow cytometry with dramatically enhanced performance and ease of use.

Developing image processing meta-algorithms with data mining of multiple metrics.

People often use multiple metrics in image processing, but here we take a novel approach of mining the values of batteries of metrics on image processing results. We present a case for extending image processing methods to incorporate automated mining of multiple image metric values. Here by a metric we mean any image similarity or distance measure, and in this paper we consider intensity-based and statistical image measures and focus on registration as an image processing problem. We show how it is possible to develop meta-algorithms that evaluate different image processing results with a number of different metrics and mine the results in an automated fashion so as to select the best results. We show that the mining of multiple metrics offers a variety of potential benefits for many image processing problems, including improved robustness and validation.

Topological object types for morphodynamic modeling languages

We survey useful ingredients for a new class of mathematical process-modeling languages aimed at spatial and developmental biology. Existing modeling languages for computational systems biology do not fully address the problems of spatial modeling that arise in morphodynamics (the local dynamics of form) and its applications to biological development. We seek to extend the operator algebra semantics approach from our previous “Dynamical Grammars” modeling language, whose most spatial object type is the labelled graph, to encompass more flexible topological objects. Taking clues from current developments in 3D meshing and from topological modeling for biology, illustrated by a plant tissue example, we seek language support for the approximation of low-dimensional CW complexes (which are nontrivial topological spaces, with cardinality of the continuum) and dynamic fields thereon, by finite labelled abstract complexes. Some of the proposed types would be computationally demanding, without further restriction. Restrictions and control of these approximations can be specified by use of “metricated” types. Minimally, such approximations should permit the accurate simulation of spatial diffusion processes.