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Chennu, A.

Publications and source records attributed to Chennu, A..

2 recordsLinked to original sources

The interplay between light, arsenic and H2O2 controls oxygenic photosynthesis in a Precambrian analog cyanobacterial mat.

The delayed rise of atmospheric oxygen, despite the early evolution of oxygenic photosynthesis (OP), remains a central puzzle in Earth history. Numerous ecological and geochemical constraints on OP have been proposed, but the role of environmental stressors at the physiological and ecosystem level is poorly understood. Here we show that Chl-f-harboring cyanobacteria in a high-altitude Andean microbial mat - an analog for Precambrian ecosystems - switch from OP to arsenite-driven anoxygenic photosynthesis (AP) under high light. Using microsensor profiling, mat incubations, and metatranscriptomics, we show that this shift is triggered by the accumulation of reactive oxygen species (ROS), especially hydrogen peroxide, which suppresses OP. Instead of ceasing activity, cyanobacteria reroute electron flow, using arsenite as the electron donor to sustain photosynthesis while avoiding both intracellular ROS from OP and extracellular ROS from aerobic arsenite oxidation. This switch is reversible and coordinated with diel cycles of light and arsenic speciation, sustained by a cryptic arsenic redox cycle, continuously regenerating arsenite for AP. Although the enzymatic basis remains unresolved, these findings reveal a hidden layer of metabolic plasticity in cyanobacteria and suggest that oxidative stress-responsive metabolic shifts may have supported early phototroph survival while limiting oxygen release - potentially contributing to Earths protracted oxygenation.

biochemistry↗

Digitizing the coral reef: machine learning of underwater spectral images enables dense taxonomic mapping of benthic habitats

O_LICoral reefs are the most biodiverse marine ecosystems, and host a wide range of taxonomic diversity in a complex spatial habitat structure. Existing coral reef survey methods struggle to accurately capture the taxonomic detail within the complex spatial structure of benthic communities. C_LIO_LIWe propose a workflow to leverage underwater hyperspectral transects and two machine learning algorithms to produce dense habitat maps of 1150 m2 of reefs across the Curacao coastline. Our multi-method workflow labelled all 500+ million pixels with one of 43 classes at taxonomic family, genus or species level for corals, algae, sponges, or to substrate labels such as sediment, turf algae and cyanobacterial mats. C_LIO_LIWith low annotation effort (2% pixels) and no external data, our workflow enables accurate (Fbeta 87%) survey-scale mapping, with unprecedented thematic and spatial detail. Our assessments of the composition and configuration of the benthic communities of 23 transect showed high consistency. C_LIO_LIDigitizing the reef habitat structure enables validation and novel analysis of pattern and scale in coral reef ecology. Our dense habitat maps reveal the inadequacies of point sampling methods to accurately describe reef benthic communities. C_LI

ecology↗