Biology subjects

Goldman, A. L.

Publications and source records attributed to Goldman, A. L..

4 recordsLinked to original sources

bioRxiv2023

CO2 Reduction by the Iron Nitrogenase Competes with N2 Fixation Under Physiological Conditions

Nitrogenases are the only known enzymes that reduce molecular nitrogen (N2) to ammonia. Recent findings have demonstrated that nitrogenases also reduce the greenhouse gas carbon dioxide (CO2), suggesting CO2 to be a competitor of N2. Intriguingly, nitrogenase isoforms (i.e., molybdenum (Mo), vanadium and iron (Fe) nitrogenase) differ significantly in their ability to reduce CO2, but the mechanisms underlying these differences remain elusive. Here, we study the competing reduction of CO2 and N2 by the two nitrogenases of Rhodobacter capsulatus, the Mo and Fe nitrogenase. Analyzing their full CO2 reduction product spectrum in vitro, we find the Fe nitrogenase almost three-fold more efficient in CO2 reduction than the Mo isoform. Furthermore, the in vitro competition experiments reveal the Fe nitrogenase to be profoundly less selective for the reduction of N2 than the Mo nitrogenase. We observe the same effects in vivo, where adding CO2 drastically increases the doubling times of diazotrophically grown R. capsulatus strains that rely on the Fe nitrogenase. The Fe nitrogenase-dependent R. capsulatus strains reduce CO2 to methane under physiological conditions, highlighting the potential of the Fe nitrogenase for the biotechnological conversion of CO2 into value-added compounds. Furthermore, both products are secreted into the surrounding, potentially influencing the composition of microbial communities in Mo-deficient environments.

biochemistry↗

bioRxiv2023

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function.

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [18F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a bench to bedside translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.

neuroscience↗

bioRxiv2023

Smaug regulates germ plasm synthesis and primordial germ cell number in Drosophila embryos by repressing the oskar and bruno 1 mRNAs

During Drosophila oogenesis, the Oskar (OSK) RNA-binding protein (RBP) determines the amount of germ plasm that assembles at the posterior pole of the oocyte. Here we identify the mechanisms that regulate the osk mRNA in the early embryo. We show that the Smaug (SMG) RBP is transported into the germ plasm of the early embryo where it accumulates in the germ granules. SMG binds to and represses translation of the osk mRNA itself as well as the bruno 1 (bru1) mRNA, which encodes an RBP that we show promotes germ plasm production. Loss of SMG or mutation of SMGs binding sites in the osk or bru1 mRNAs results in ectopic translation of these transcripts in the germ plasm and excess PGCs. SMG therefore triggers a post-transcriptional regulatory pathway that attenuates germ plasm synthesis in embryos, thus modulating the number of PGCs.

developmental biology↗

bioRxiv2023

Microbial sensor variation across biogeochemical conditions in the terrestrial deep subsurface

Microbes can be found in abundance many kilometers underground. While microbial metabolic capabilities have been examined across different geochemical settings, it remains unclear how changes in subsurface niches affect microbial needs to sense and respond to their environment. To address this question, we examined how two component systems (TCS) vary across metagenomes in the Deep Mine Microbial Observatory (DeMMO). TCSs were found at all six subsurface sites, the service water control, and the surface site, with an average of 0.88 sensor histidine kinases (HKs) per 100 genes across all sites. Abundance was greater in subsurface fracture fluids compared with surface-derived fluids, and candidate phyla radiation (CPR) bacteria presented the lowest HK frequencies. Measures of microbial diversity, such as the Shannon diversity index, revealed that HK abundance is inversely correlated with microbial diversity (r2 = 0.81). Among the geochemical parameters measured, HK frequency correlated the strongest with variance in dissolved organic carbon (DOC) (r2 = 0.82). Taken together, these results implicate the abiotic and biotic properties of an ecological niche as drivers of sensor needs, and they suggest that microbes in environments with large fluctuations in organic nutrients (e.g., lacustrine, terrestrial, and coastal ecosystems) may require greater TCS diversity than ecosystems with low nutrients (e.g., open ocean). IMPORTANCEThe ability to detect environmental conditions is a fundamental property of all life forms. However, organisms do not maintain the same environmental sensing abilities during evolution. To better understand the controls on microbial sensor abundance, which remain poorly understood, we evaluated how two-component sensor systems evolved within the deep Earth across sampling sites where abiotic and biotic properties vary. We quantify the relative abundances of sensor proteins and find that sensor systems remain abundant in microbial consortia as depth below the Earths surface increases. We also observe correlations between sensor system abundances and abiotic (dissolved organic carbon variation) and biotic (consortia diversity) properties across the DeMMO sites. These results suggest that multiple environmental properties drive sensor protein evolution and diversification and highlight the importance of studying metagenomic and geochemical data in parallel to understand the drivers of microbial sensor evolution.

microbiology↗