GUSignal: An Informatics Tool to Analyze Glucuronidase Gene Expression in Arabidopsis Thaliana Roots.

The uidA gene codifies for a glucuronidase (GUS) enzyme which has been used as a biotechnological tool during the last years. When uidA gene is fused to a gene's promotor region, it is possible to evaluate the activity of this one in response to a stimulus. Arabidopsis thaliana has served as the biological platform to elucidate molecular and regulatory signaling responses in plants. Transgenic lines of A. thaliana, tagged with the uidA gene, have allowed explaining how plants modify their hormonal pathways depending on the environmental conditions. Although the information extracted from microscopic images of these transgenic plants is often qualitative and in many publications is not subjected to quantification, in this paper we report the development of an informatics tool focused on computer vision for processing and analysis of digital images in order to analyze the expression of the GUS signal in A. thaliana roots, which is strongly correlated with the intensity of the grayscale images. This means that the presence of the GUS-induced color indicates where the gene has been actively expressed, such as our statistical analysis has demonstrated after treatment of A. thaliana DR5::GUS with naphtalen-acetic acid (0.0001 mM and 1 mM). GUSignal is a free informatics tool that aims to be fast and systematic during the image analysis since it executes specific and ordered instructions, to offer a segmented analysis by areas or regions of interest, providing quantitative results of the image intensity levels.

NIFtHool: an informatics program for identification of NifH proteins using deep neural networks.

Atmospheric nitrogen fixation carried out by microorganisms has environmental and industrial importance, related to the increase of soil fertility and productivity. The present work proposes the development of a new high precision system that allows the recognition of amino acid sequences of the nitrogenase enzyme (NifH) as a promising way to improve the identification of diazotrophic bacteria. For this purpose, a database obtained from UniProt built a processed dataset formed by a set of 4911 and 4782 amino acid sequences of the NifH and non-NifH proteins respectively. Subsequently, the feature extraction was developed using two methodologies: (i) k-mers counting and (ii) embedding layers to obtain numerical vectors of the amino acid chains. Afterward, for the embedding layer, the data was crossed by an external trainable convolutional layer, which received a uniform matrix and applied convolution using filters to obtain the feature maps of the model. Finally, a deep neural network was used as the primary model to classify the amino acid sequences as NifH protein or not. Performance evaluation experiments were carried out, and the results revealed an accuracy of 96.4%, a sensitivity of 95.2%, and a specificity of 96.7%. Therefore, an amino acid sequence-based feature extraction method that uses a neural network to detect N-fixing organisms is proposed and implemented. NIFtHool is available from: https://nifthool.anvil.app/.

High-Up: A Remote Reservoir of Microbial Extremophiles in Central Andean Wetlands.

The Central Andes region displays unexplored ecosystems of shallow lakes and salt flats at mean altitudes of 3700 m. Being isolated and hostile, these so-called "High-Altitude Andean Lakes" (HAAL) are pristine and have been exposed to little human influence. HAAL proved to be a rich source of microbes showing interesting adaptations to life in extreme settings (poly-extremophiles) such as alkalinity, high concentrations of arsenic and dissolved salts, intense dryness, large daily ambient thermal amplitude, and extreme solar radiation levels. This work reviews HAAL microbiodiversity, taking into account different microbial niches, such as plankton, benthos, microbial mats and microbialites. The modern stromatolites and other microbialites discovered recently at HAAL are highlighted, as they provide unique modern-though quite imperfect-analogs of environments proxy for an earlier time in Earth's history (volcanic setting and profuse hydrothermal activity, low atmospheric O2 pressure, thin ozone layer and high UV exposure). Likewise, we stress the importance of HAAL microbes as model poly-extremophiles in the study of the molecular mechanisms underlying their resistance ability against UV and toxic or deleterious chemicals using genome mining and functional genomics. In future research directions, it will be necessary to exploit the full potential of HAAL poly-extremophiles in terms of their biotechnological applications. Current projects heading this way have yielded detailed molecular information and functional proof on novel extremoenzymes: i.e., DNA repair enzymes and arsenic efflux pumps for which medical and bioremediation applications, respectively, are envisaged. But still, much effort is required to unravel novel functions for this and other molecules that dwell in a unique biological treasure despite its being hidden high up, in the remote Andes.