Biology subjects

Mestre, M.

Publications and source records attributed to Mestre, M..

5 recordsLinked to original sources

bioRxiv2024

Base-modified nucleotides mediate immune signaling in bacteria

Signaling from pathogen sensing to effector activation is a fundamental principle of cellular immunity. While cyclic (oligo)nucleotides have emerged as key signaling molecules, the existence of other messengers remains largely unexplored. Here, we reveal a bacterial anti-phage system that mediates immune signaling through nucleobase modification. Immunity is triggered by phage nucleotide kinases, which, combined with the system-encoded adenosine deaminase, produce deoxyinosine 5-triphosphate (dITP) as immune messengers. The dITP signal activates downstream effector to mediate cellular NAD+ depletion, resulting in population-level defense through the death of infected cells. To counteract immune signaling, phages deploy specialized enzymes that deplete cellular dAMP, the precursor of dITP messengers. Our findings uncover a nucleobase modification-based anti-phage signaling pathway, establishing noncanonical nucleotides as a new type of immune messengers in bacteria.

microbiology↗

bioRxiv2024

Landscape-scale spatial variations of pre-Columbian anthropogenic disturbances at three ring ditch sites in French Guiana

In the past two decades, repeated discoveries of numerous geometric earthworks in interfluvial regions of Amazonia have shed new light onto the territorial extent and the long-term impact of pre-Columbian populations on contemporary landscapes. In particular, the recent development of LiDAR imagery has accelerated the discovery of earthworks in densely forested hinterlands throughout the Amazon basin and the Guiana Shield. This study aimed to evaluate the extent and landscape-scale spatial variations of pre-Columbian disturbances at three ring ditch sites in the French Guiana hinterland. We carried out extensive soil surveys along approximately 1 km-long transects spanning from ring ditches through the surrounding landscapes, and drawn upon multiple indicators, including archaeological artifacts, macro- and micro-charcoals, soil colorimetry, and physicochemical properties to retrace the pre-Columbian history of these sites in terms of occupation periods, anthropogenic soil alteration, and ancient land use. Our results revealed a perennial occupation of these sites over long periods ranging from the 5th and 15th centuries CE, with local enrichments in chemical indicators (Corg, N, Mg, K, Ca) both within the enclosures of ring ditches and in the surrounding landscapes. Physicochemical properties variations were accompanied by variations in soil colorimetry, with darker soils within the enclosure of ring ditches in terra-firme areas. Interestingly however, soil properties did not meet all the characteristics of the so-called Amazonian Dark Earths, thus advocating a paradigm shift towards a better integration of Amazonian Brown Earths into the definition of anthropogenic soils in Amazonia. Soil disturbances were also associated to local enrichments in macro- and micro-charcoals that support in situ fire management that could be attributed to forest clearance and/or slash-and-burn cultivation. Taken together, our results support the idea that pre-Columbian societies made extensive use of their landscapes in the interfluvial regions of the French Guiana hinterlands.

ecology↗

bioRxiv2023

Global biogeography of the smallest plankton across ocean depths

Tiny ocean plankton (picoplankton) are fundamental for the functioning of the biosphere, but the ecological mechanisms shaping their biogeography are partially understood. Comprehending whether these microorganisms are structured by niche vs. neutral processes is highly relevant in the context of global change. The ecological drivers structuring picoplankton communities differ between prokaryotes and minute eukaryotes (picoeukaryotes) in the global surface ocean: while prokaryotic communities are shaped by a balanced combination of dispersal, selection, and drift, picoeukaryotic communities are mainly shaped by dispersal limitation. Yet, whether or not the relative importance of these processes in structuring picoplankton varies as we dive into the deep ocean was unknown. Here we investigate the mechanisms structuring picoplanktonic communities inhabiting different ocean depths. We analyzed 451 samples from the tropical and subtropical global ocean and the Mediterranean Sea covering the epi- (0-200m), meso- (200- 1,000m), and bathypelagic (1,000-4,000m) depth zones. We found that selection decreased with depth possibly due to lower habitat heterogeneity. In turn, dispersal limitation increased with depth, possibly due to dispersal barriers such as water masses and bottom topography. Picoplankton {beta}-diversity positively correlated with environmental heterogeneity and water mass variability in both the open-ocean and the Mediterranean Sea. However, this relationship tended to be weaker for picoeukaryotes than for prokaryotes. Community patterns were generally more pronounced in the Mediterranean Sea, probably because of its substantial cross-basin environmental heterogeneity and deep-water isolation. Altogether, we found that different combinations of ecological mechanisms shape the biogeography of the smallest members of the ocean microbiome across ocean depths.

ecology↗

bioRxiv2022

A general deep hybrid model for bioreactor systems: combining first Principles equations with deep neural networks

Numerous studies have reported the use of hybrid semiparametric systems that combine shallow neural networks with mechanistic models for bioprocess modeling. Here we revisit the general bioreactor hybrid modeling problem and introduce some of the most recent deep learning techniques. The single layer networks were extended to multi-layer networks with varying depths and combined with First Principles equations in the form of deep hybrid models. Deep learning techniques, namely the adaptive moment estimation method (ADAM), stochastic regularization and depth-dependent weights initialization were evaluated. Modified sensitivity equations are proposed for the computation of gradients in order to reduce CPU time for the training of deep hybrid models. The methods are illustrated with applications to a synthetic dataset and a pilot 50 L MUT+ Pichia pastoris process expressing a single chain antibody fragment. All in all, the results point to a systematic generalization improvement of deep hybrid models over its shallow counterpart. Moreover, the CPU cost to train the deep hybrid models is shown to be lower than for the shallow counterpart. In the pilot 50L MUT+ Pichia pastoris data set, the prediction accuracy was increased by 18.4% and the CPU decreased by 43.4%. HighlightsO_LIShallow hybrid models have been widely used for bioprocess modeling and optimization C_LIO_LINon-deep training using e.g. the Levenberg - Marquardt method, cross-validation and indirect sensitivity equations have been the methods of choice C_LIO_LIDeep learning with ADAM, stochastic regularization and indirect sensitivity significantly reduces the training CPU C_LIO_LIThe generalization capacity of deep hybrid models systematically outperforms that of shallow hybrid models C_LI

systems biology↗

bioRxiv2018

Different processes shape prokaryotic and picoeukaryotic assemblages in the sunlit ocean microbiome

The smallest members of the sunlit-ocean microbiome (prokaryotes and picoeukaryotes) participate in a plethora of ecosystem functions with planetary-scale effects. Understanding the processes determining the spatial turnover of this assemblage can help us better comprehend the links between microbiome species composition and ecosystem function. Ecological theory predicts that selection, dispersal and drift are main drivers of species distributions, yet, the relative quantitative importance of these ecological processes in structuring the surface-ocean microbiome is barely known. Here we quantified the role of selection, dispersal and drift in structuring surface-ocean prokaryotic and picoeukaryotic assemblages by using community DNA-sequence data collected during the global Malaspina expedition. We found that dispersal limitation was the dominant process structuring picoeukaryotic communities, while a balanced combination of dispersal limitation, selection and drift shaped prokaryotic counterparts. Subsequently, we determined the agents exerting abiotic selection as well as the spatial patterns emerging from the action of different ecological processes. We found that selection exerted via temperature had a strong influence on the structure of prokaryotic communities, particularly on species co-occurrences, a pattern not observed among communities of picoeukaryotes. Other measured abiotic variables had limited selective effects on microbiome structure. Picoeukaryotes presented a higher differentiation between neighbouring communities and a higher distance-decay when compared to prokaryotes, agreeing with their higher dispersal limitation. Finally, drift seemed to have a limited role in structuring the sunlit-ocean microbiome. The different predominance of ecological processes acting on particular subsets of the ocean microbiome suggests uneven responses to environmental change.\n\nSIGNIFICANCE STATEMENTThe global ocean contains one of the largest microbiomes on Earth and changes on its structure can impact the functioning of the biosphere. Yet, we are far from understanding the mechanisms that structure the global ocean microbiome, that is, the relative importance of environmental selection, dispersal and random events (drift). We evaluated the role of these processes at the global scale, based on data derived from a circumglobal expedition and found that these ecological processes act differently on prokaryotes and picoeukaryotes, two of the main components of the ocean microbiome. Our work represents a significant contribution to understand the assembly of marine microbial communities, providing also insights on the links between ecological mechanisms, microbiome structure and ecosystem function.

ecology↗