Tissue structure accelerates evolution premalignant sweeps precede neutral expansion, bioRxiv, 2019-02-11

Cancer has been hypothesized to be a caricature of the renewal process of the tissue of origin arising from (and maintained by) small subpopulations capable of continuous growth1. The strong influence of the tissue structure has been convincingly demonstrated in intestinal cancers where adenomas grow by the fission of stem-cell-maintained glands influenced by early expression of abnormal cell mobility in cancer progenitors2, 3. So-called “born to be bad” tumors arise from progenitors which may already possess the necessary driver mutations for malignancy4, 5 and metastasis6. These tumors subsequently evolve neutrally, thereby maximizing intratumoral heterogeneity and increasing the probability of therapeutic resistance. These findings have been nuanced by the advent of multi-region sequencing, which uses spatial and temporal patterns of genetic variation among competing tumor cell populations to shed light on the mode of tumor evolution (neutral or Darwinian) and also the tempo4, 7–11. Using a classic, well-studied model of tumor evolution (a passenger-driver mutation model12–16) we systematically alter spatial constraints and cell mixing rates to show how tissue structure influences functional (driver) mutations and genetic heterogeneity over time. This model approach explores a key mechanism behind both inter-patient and intratumoral tumor heterogeneity competition for space. Initial spatial constraints determine the emergent mode of evolution (Darwinian to neutral) without a change in cell-specific mutation rate or fitness effects. Driver acquisition during the Darwinian precancerous stage may be accelerated en route to neutral evolution by the combination of two factors spatial constraints and limited cellular mixing.

biorxiv cancer-biology 0-100-users 2019

Object Detection Networks and Augmented Reality for Cellular Detection in Fluorescence Microscopy Acquisition and Analysis, bioRxiv, 2019-02-09

AbstractIn this paper we demonstrate the application of object detection networks for the classification and localization of cells in fluorescence microscopy. We benchmark two leading object detection algorithms across multiple challenging 2-D microscopy datasets as well as develop and demonstrate an algorithm which can localize and image cells in 3-D, in real-time. Furthermore, we exploit the fast processing of these algorithms and develop a simple and effective Augmented Reality (AR) system for fluorescence microscopy systems. Object detection networks are well-known high performance networks famously applied to the task of identifying and localizing objects in photography images. Here we show their application and efficiency for localizing cells in fluorescence microscopy images. Object detection algorithms are typically trained on many thousands of images, which can be prohibitive within the biological sciences due to the cost of imaging and annotating large amounts of data. Through taking different cell types and assays as an example, we show that with some careful considerations it is possible to achieve very high performance with datasets with as few as 26 images present. Using our approach, it is possible for relatively non-skilled users to automate detection of cell classes with a variety of appearances and enable new avenues for automation of conventionally manual fluorescence microscopy acquisition pipelines.

biorxiv bioinformatics 0-100-users 2019

Auxin export from proximal fruits drives arrest in competent inflorescence meristems, bioRxiv, 2019-02-06

A well-defined set of regulatory pathways control entry into the reproductive phase in flowering plants. Conversely, little is known about the mechanisms that control the end of the reproductive phase (floral arrest), despite this being a critical process for optimising fruit and seed production. Complete fruit removal or lack of fertile fruit-set in male sterile mutants, for example male sterile1 (ms1), prevents timely floral arrest in the model plant Arabidopsis. These observations formed the basis for Hensel and colleagues model in which end-of-flowering was proposed to result from a cumulative fruitseed-derived signal that caused simultaneous global proliferative arrest (GPA) in all inflorescences. Recent studies have suggested that end-of-flowering involves gene expression changes at the floral meristem which are at least in part controlled by the FRUITFULL-APETELA2 pathway, however there is limited understanding of how this process is controlled and the communication needed at the whole plant level. Here, we provide new information providing a framework for the fruit-to-meristem (F-M) communication implied by the GPA model. We show that floral arrest in Arabidopsis is not global and does not occur synchronously between branches, but rather that the arrest of each inflorescence is a local process, driven by auxin export from fruit proximal to the inflorescence meristem (IM). Furthermore, we show that inflorescence meristems are only competent for floral arrest once they reach a certain developmental age. Understanding the regulation of floral arrest is of major importance for the future manipulation of flowering to extend and maximise crop yields.

biorxiv plant-biology 0-100-users 2019

 

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