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Data include soil and litter measurements for moisture, pH, and carbon-to-nitrogen ratio. Samples were collected from 8 different ecoregions, as determined by NEON, at various NEON/LTER and/or other experimental sites. Soil cores and litter samples were taken in the spring and fall of 2022. 

The concept that proteins are selected to fold into a well-defined native state has been effectively addressed within the framework of energy landscapes, underpinning the recent successes of structure prediction tools like AlphaFold. The amyloid fold, however, does not represent a unique minimum for a given single sequence. While the cross-βhydrogen-bonding pattern is common to all amyloids, other aspects of amyloid fiber structures are sensitive not only to the sequence of the aggregating peptides but also to the experimental conditions. This polymorphic nature of amyloid structures challenges structure predictions. In this paper, we use AI to explore the landscape of possible amyloid protofilament structures composed of a single stack of peptides aligned in a parallel, in-register manner. This perspective enables a practical method for predicting protofilament structures of arbitrary sequences: RibbonFold. RibbonFold is adapted from AlphaFold2, incorporating parallel in-register constraints within AlphaFold2’s template module, along with an appropriate polymorphism loss function to address the structural diversity of folds. RibbonFold outperforms AlphaFold2/3 on independent test sets, achieving a mean TM-score of 0.5. RibbonFold proves well-suited to study the polymorphic landscapes of widely studied sequences with documented polymorphisms. The resulting landscapes capture these observed polymorphisms effectively. We show that while well-known amyloid-forming sequences exhibit a limited number of plausible polymorphs on their “solubility” landscape, randomly shuffled sequences with the same composition appear to be negatively selected in terms of their relative solubility. RibbonFold is a valuable framework for structurally characterizing amyloid polymorphism landscapes. 

Chromatin is partially structured through the effects of biological motors. “Swimming motors” such as RNA polymerases and chromatin remodelers are thought to act differentially on the active parts of the genome and the stored inactive part. By systematically expanding the many-body master equation for chromosomes driven by swimming motors, we show that this nonuniform aspect of motorization leads to heterogeneously folded conformations, thereby contributing to chromosome compartmentalization. 

Despite being present in many North American forest understories, the ectomycorrhizal (ECM) fungal communities associated with Corylus shrubs have received no prior study. To address this knowledge gap, we characterized the ECM fungal communities on roots of Corylus shrubs as well as co-occurring Quercus and Pinus trees in Minnesota, USA. ECM-colonized root tips from pairs of Corylus shrubs and four ECM tree species, Quercus macrocarpa, Quercus ellipsoidalis, Pinus strobus, and Pinus resinosa, growing in close proximity (<1 m), were sampled at the Cedar Creek Ecosystem Science Reserve. ECM fungal communities were assessed using high-throughput sequencing of the ITS2 region. ECM fungal operational taxonomic unit (OTU) richness was equivalent among the two Quercus species and their associated Corylus shrubs, but significantly higher on P. strobus–associated Corylus shrubs compared with P. strobus, P. resinosa, and P. resinosa–associated Corylus shrubs. ECM fungal community composition on Corylus shrubs largely mirrored that on each of the Quercus and Pinus species, although the two Pinus commu- nities were significantly different from each other. Further, the same ECM fungal OTUs were commonly encountered on paired Corylus–tree host samples, suggesting a high potential for co- colonization by the same fungal individuals. Collectively, these results support the growing consensus that woody understory plants often associate with similar ECM fungal communities as co-occurring tree hosts regardless of phylogenetic relatedness 

ABSTRACT Bacteria are major drivers of organic matter decomposition and play crucial roles in global nutrient cycling. Although the degradation of dead fungal biomass (necromass) is increasingly recognized as an important contributor to soil carbon (C) and nitrogen (N) cycling, the genes and metabolic pathways involved in necromass degradation are less characterized. In particular, how bacteria degrade necromass containing different quantities of melanin, which largely control rates of necromass decompositionin situ, is largely unknown. To address this gap, we conducted a multi-timepoint transcriptomic analysis using three Gram-negative, bacterial species grown on low or high melanin necromass ofHyaloscypha bicolor. The bacterial species,Cellvibrio japonicus, Chitinophaga pinensis, andSerratia marcescens, belong to genera known to degrade necromassin situ. We found that while bacterial growth was consistently higher on low than high melanin necromass, the CAZyme-encoding gene expression response of the three species was similar between the two necromass types. Interestingly, this trend was not shared for genes encoding nitrogen utilization, which varied inC. pinensisandS. marcescensduring growth on high vs low melanin necromass. Additionally, this study tested the metabolic capabilities of these bacterial species to grow on a diversity of C and N sources and found that the three bacteria have substantially different utilization patterns. Collectively, our data suggest that as necromass changes chemically over the course of degradation, certain bacterial species are favored based on their differential metabolic capacities.IMPORTANCEFungal necromass is a major component of the carbon (C) in soils as well as an important source of nitrogen (N) for plant and microbial growth. Bacteria associated with necromass represent a distinct subset of the soil microbiome and characterizing their functional capacities is the critical next step toward understanding how they influence necromass turnover. This is particularly important for necromass varying in melanin content, which has been observed to control the rate of necromass decomposition across a variety of ecosystems. Here we assessed the gene expression of three necromass-degrading bacteria grown on low or high melanin necromass and characterized their metabolic capacities to grow on different C and N substrates. These transcriptomic and metabolic studies provide the first steps toward assessing the physiological relevance of up-regulated CAZyme-encoding genes in necromass decomposition and provide foundational data for generating a predictive model of the molecular mechanisms underpinning necromass decomposition by soil bacteria. 

Electron transfer is at the heart of many fundamental physical, chemical, and biochemical processes essential for life. The exact simulation of these reactions is often hindered by the large number of degrees of freedom and by the essential role of quantum effects. Here, we experimentally simulate a paradigmatic model of molecular electron transfer using a multispecies trapped-ion crystal, where the donor-acceptor gap, the electronic and vibronic couplings, and the bath relaxation dynamics can all be controlled independently. By manipulating both the ground-state and optical qubits, we observe the real-time dynamics of the spin excitation, measuring the transfer rate in several regimes of adiabaticity and relaxation dynamics. Our results provide a testing ground for increasingly rich models of molecular excitation transfer processes that are relevant for molecular electronics and light-harvesting systems.