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Disentangling the feedback loops driving spatial patterning in microbial communities
Abstract
The properties of multispecies biofilms are determined by how species are arranged in space. How these patterns emerge is a complex and largely unsolved problem. Here, we synthesize the known factors affecting pattern formation, identify the interdependencies and feedback loops coupling them, and discuss approaches to disentangle their effects. Finally, we propose an interdisciplinary research program that could create a predictive understanding of pattern formation in microbial communities.
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Microbial Ecology to Ocean Carbon Cycling: From Genomes to Numerical Models
Abstract
The oceans contain large reservoirs of inorganic and organic carbon and play a critical role in both global carbon cycling and climate. Most of the biogeochemical transformations in the oceans are driven by marine microbes. Thus, molecular processes occurring at the scale of single cells govern global geochemical dynamics, posing a challenge of scales. Understanding the processes controlling ocean carbon cycling from the cellular to the global scale requires the integration of multiple disciplines including microbiology, ecology, biogeochemistry, and computational fields such as numerical models and bioinformatics. A shared language and foundational knowledge will facilitate these interactions. This review provides the state of knowledge on the role marine microbes play in large-scale ocean carbon cycling through the lens of observational oceanography and biogeochemical models. We conclude by outlining ways in which the field can bridge the gap between -omics datasets and ocean models to understand ocean carbon cycling across scales.
- -Omic approaches are providing increasingly quantitative insight into the biogeochemical functions of marine microbial ecosystems.
- Numerical models provide a tool for studying global carbon cycling by scaling from the microscale to the global scale.
- The integration of -omics and numerical modeling generates new understanding of how microbial metabolisms and community dynamics set nutrient fluxes in the ocean.
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Mechanistic Insights Into Post-Translational α-Keto-β-Amino Acid Formation by a Radical S-Adenosyl Methionine Peptide Splicease
Abstract
Radical S-adenosyl methionine enzymes catalyze a diverse repertoire of post-translational modifications in protein and peptide substrates. Among these, an exceptional and mechanistically obscure example is the installation of α-keto-β-amino acid residues by formal excision of a tyrosine-derived tyramine unit. The responsible spliceases are key maturases in a widespread family of natural products termed spliceotides that comprise potent protease inhibitors, with the installed β-residues
being crucial for bioactivity. Here, we established the in vitro activity of the model splicease PcpXY to interrogate the mechanism of non-canonical protein splicing. Identification of shunt and coproducts, deuterium labeling studies, and density functional theory energy calculations of hypothesized intermediates support a mechanism involving hydrogen abstraction at tyrosine Cα as the initial site of peptide radical formation and release of 4-hydroxybenzaldehyde as the tyrosine-derived coproduct. The data illuminate key features of this unprecedented radical-mediated biotransformation yielding ketoamide pharmacophores that are also present in peptidomimetic therapeutics. -
Slower swimming promotes chemotactic encounters between bacteria and small phytoplankton
Abstract
Chemotaxis enables marine bacteria to increase encounters with phytoplankton cells by reducing their search times, provided that bacteria detect noisy chemical gradients around phytoplankton. Gradient detection depends on bacterial phenotypes and phytoplankton size: large phytoplankton produce spatially extended but shallow gradients, whereas small phytoplankton produce steeper but spatially more confined gradients. To date, it has remained unclear how phytoplankton size and bacterial swimming speed affect bacteria’s gradient detection ability and search times for phytoplankton. Here, we compute an upper bound on the increase in bacterial encounter rate with phytoplankton due to chemotaxis over random motility alone. We find that chemotaxis can substantially decrease search times for small phytoplankton, but this advantage is highly sensitive to variations in bacterial phenotypes or phytoplankton leakage rates. By contrast, chemotaxis toward large phytoplankton cells reduces the search time more modestly, but this benefit is more robust to variations in search or environmental parameters. Applying our findings to marine phytoplankton communities, we find that, in productive waters, chemotaxis toward phytoplankton smaller than 2 μm provides little to no benefit, but can decrease average search times for large phytoplankton (∼20 μm) from 2 wk to 2 d, an advantage that is robust to variations and favors bacteria with higher swimming speeds. By contrast, in oligotrophic waters, chemotaxis can reduce search times for picophytoplankton (∼1 μm) up to 10-fold, from a week to half a day, but only for bacteria with low swimming speeds and long sensory timescales. This asymmetry may promote the coexistence of diverse search phenotypes in marine bacterial populations.