Biology subjects

Klatt, J.

Publications and source records attributed to Klatt, J..

3 recordsLinked to original sources

bioRxiv2025

Seasonal biogeochemical variations in a modern microbialite reef under early Earth-like conditions

Microbialites are organosedimentary structures dating to the Precambrian that serve as archives of Earths environmental evolution. Today, they persist in only a few environments markedly different from those in which they first arose. Here, we report a modern microbialite reef in Laguna Pozo Bravo (Puna region, Argentina), exposed to high radiation, low oxygen pressure, and volcanic inputs reminiscent of early Earth. Through physicochemical, mineralogical, spectroscopic, electron microscopy, and metagenomic analyses, we identified diverse microbial communities with metabolic capacities that induce mineralisation. Seasonal environmental fluctuations drive cyclical changes in community composition, producing potential mineralisation patterns. Our findings suggest that carbon fixation and the metabolic drivers of alkalinity in microbialites evolved over time. Moreover, the variability in prokaryotic compositions among modern microbialites demonstrates that carbonate precipitation is governed by metabolic potential rather than taxonomy, reinforcing their role as dynamic records of environmental conditions.

microbiology↗

bioRxiv2024

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↗

bioRxiv2021

networkGWAS: A network-based approach for genome-wide association studies in structured populations

While the search for associations between genetic markers and complex traits has led to the discovery of tens of thousands of trait-related genetic variants, the vast majority of these only explain a small fraction of observed phenotypic variation. One possible strategy to detect stronger associations is to aggregate the effects of several genetic markers and to test entire genes, pathways or (sub)networks of genes for association to a phenotype. The latter, network-based genome-wide association studies, in particular suffers from a vast search space and an inherent multiple testing problem. As a consequence, current approaches are either based on greedy feature selection, thereby risking that they miss relevant associations, or neglect doing a multiple testing correction, which can lead to an abundance of false positive findings. To address the shortcomings of current approaches of network-based genome-wide association studies, we propose networkGWAS, a computationally efficient and statistically sound approach to network-based genome-wide association studies using mixed models and neighborhood aggregation. It allows for population structure correction and for well-calibrated p-values, which are obtained through circular and degree-preserving network permutation schemes. networkGWAS successfully detects known associations on semi-simulated common variants from A. thaliana and on simulated rare variants from H. sapiens, as well as neighborhoods of genes involved in stress-related biological processes on a stress-induced phenotype from S. cerevisiae. It thereby enables the systematic combination of gene-based genome-wide association studies with biological network information. Availabilityhttps://github.com/BorgwardtLab/networkGWAS.git Contactgiulia.muzio@bsse.ethz.ch, karsten.borgwardt@bsse.ethz.ch

genomics↗