Biology subjects

Nicora, C. D.

Publications and source records attributed to Nicora, C. D..

30 records · Page 2Linked to original sources

bioRxiv2023

Pumping Iron: A Multi-omics Analysis of Two Extremophilic Algae Reveals Mechanisms of Iron Economy

Marine algae are responsible for half of the worlds primary productivity, but this critical carbon sink is often constrained by insufficient iron. One species of marine algae, Dunaliella tertiolecta, is remarkable for its ability to maintain photosynthesis and thrive in low-iron environments. A related species, Dunaliella salina Bardawil, shares this attribute but is an extremophile found in hyper-saline environments. To elucidate how algae manage their iron requirements, we produced high-quality genome assemblies and transcriptomes for both species to serve as a foundation for a comparative multi-omics analysis. We identified a host of iron-uptake proteins in both species, including a massive expansion of transferrins and a novel family of siderophore-iron uptake proteins. Complementing these multiple iron-uptake routes, ferredoxin functions as a large iron reservoir that can be released by induction of flavodoxin. Proteomic analysis revealed reduced investment in the photosynthetic apparatus coupled with remodeling of antenna proteins by dramatic iron-deficiency induction of TIDI1, an LHCA-related protein found also in other chlorophytes. These combinatorial iron scavenging and sparing strategies make Dunaliella unique among photosynthetic organisms. Significance StatementDespite their small size, microalgae play a huge role in CO2 uptake via photosynthesis, and represent an important target for climate crisis mitigation efforts. Most photosynthesis proteins require iron as a co-factor so that insufficient iron often limits algal CO2 sequestration. With this in mind, we examined a genus of microalgae called Dunaliella that is exceptionally well-adapted to low iron environments. We produced complete genomes, transcriptomes, and proteomes for two species of Dunaliella that hail from radically different environments: one from coastal ocean waters and the other from salt flats. We identified dozens of genes and multiple, complementary strategies that both species utilize for iron-uptake and management that explain Dunaliellas remarkable ability to thrive on low iron.

systems biology↗

bioRxiv2022

Single cell carbon and nitrogen incorporation and remineralization profiles are uncoupled from phylogenetic groupings of diatom-associated bacteria

Bacterial remineralization of algal organic matter is thought to fuel algal growth, but this has not been quantified. Consequently, we cannot currently predict whether some bacterial taxa may provide more remineralized nutrients to algae than others, nor whether this is linked their incorporation. We quantified bacterial incorporation of algal-derived complex dissolved organic C (DOC) and N (DON) and net algal incorporation of remineralized C and N at the single cell level using isotope tracing and NanoSIMS for fifteen bacterial co-cultures growing with the diatom Phaeodactylum tricornutum. We found unexpected variability in the net C and N fluxes between algae and bacteria, including non-ubiquitous complex DON utilization and remineralization. We identified three distinct functional categories of metabolic interactions, which we termed macromolecule remineralizers, macromolecule users, and small-molecule users, the latter exhibiting efficient growth under low carbon availability. The functional categories were not linked to phylogeny and could not be elucidated strictly from metabolic capacity as predicted by comparative genomics. Using comparative proteogenomic analyses, we show that a complex DON incorporating strain expressed proteins related to growth and peptide transport, and a non-incorporator prioritized reactive oxygen species scavenging and inorganic nutrient uptake. Our analysis suggests that phylogeny does not predict the extent of algae-bacteria metabolite exchange, and activity-based measurements are indispensable to classify the high diversity of microbes into functional groups. These categorizations are useful for conceptual understanding and mechanistic numerical modeling to ultimately predict the fate of elemental cycles in response to environmental change.

microbiology↗

bioRxiv2022

Metabolic traits and the niche of bulk soil bacteria in a Mediterranean grassland

Soil microorganisms have adapted to compete and exploit different metabolic niches in their physically and chemically diverse environment via evolution and acquisition of distinct physiological and biochemical traits. As the interface for most carbon and nutrient exchange between plants and microorganisms, the rhizosphere has received substantial attention. By comparison, what is commonly termed bulk-soil (soil free of living roots) represents a far greater volume and surface area throughout the season, and substantially higher taxonomic and phylogenetic diversity; the traits and activity of its inhabitants may also have a significant impact on overall soil function. We used a combination of comparative genomics and exoproteomics to identify metabolic traits of bacteria adapted to life in bulk soil and compared these with traits of bacteria living in the rhizosphere of wild oat, Avena barbata. In bulk soil bacteria, we observed: (i) greater investment in extracellular polymer-degrading enzyme production; (ii) greater potential for secretion (presence of signal peptides) of polymer-degrading enzymes; (iii) production of accessory proteins (carbohydrate binding modules) fused with glycoside hydrolases that enhance substrate affinity, stabilize, and increase reaction rates of polymer degrading enzymes; and (iv) organization of polymer degradation machinery within gene clusters that facilitate co-transcription of enzymes, transcription factors and transporters for polymer depolymerization products. Together, these findings suggest that unlike rhizosphere-adapted bacteria--which specialize on small molecules released primarily as root exudates--bulk soil-adapted bacteria have evolved to exploit plant polymers. This biochemically costly strategy may be mitigated by protein-level adaptations that enhance the efficiency of extracellular enzyme-mediated substrate acquisition. IMPORTANCEPlant-soil-microbe interactions are dynamic and complex, with significant implications for ecosystem functioning. Microbial traits, such as nutrient acquisition and growth yield, combined with soil and climate parameters, impact major biogeochemical processes and can define the future fate of soil carbon. Diverse soil microorganisms occupy different physical habitats within soil and exploit distinct niches by expressing different metabolic traits. Identifying and quantifying traits that underlie their fitness and function is key for understanding and predicting how soil carbon transformation and stabilization will change in the future or can be managed through intervention.

microbiology↗

bioRxiv2022

Targeted curation of the gut microbial gene content modulating human cardiovascular disease

Despite the promise of the gut microbiome to forecast human health, few studies expose the microbial functions underpinning such predictions. To comprehensively inventory gut microorganisms and their gene content that control trimethylamine induced cardiovascular disease, we mined over 200,000 gut-derived genomes from cultivated and uncultivated microbial lineages. Creating MAGICdb (Methylated Amine Gene Inventory of Catabolism database), we designated an atherosclerotic profile for 6,341 microbial genomes that encoded metabolisms associated with heart disease. We used MAGICdb to evaluate diverse human fecal metatranscriptome and metaproteome datasets, demonstrating how this resource eases the recovery of methylated amine gene content previously obscured in microbiome datasets. From the feces of healthy and diseased subjects, we show MAGICdb gene markers predicted cardiovascular disease as effectively as traditional blood diagnostics. This functional microbiome catalog is a public, exploitable resource, enabling a new era of microbiota-based therapeutics.

genomics↗

bioRxiv2022

Genome-resolved metaproteomics decodes the microbial and viral contributions to coupled carbon and nitrogen cycling in river sediments

Rivers have a significant role in global carbon and nitrogen cycles, serving as a nexus for nutrient transport between terrestrial and marine ecosystems. Although rivers have a small global surface area, they contribute substantially to global greenhouse gas emissions through microbially mediated processes within the river hyporheic zone. Despite this importance, microbial roles in these climatically relevant systems are mostly inferred from 16S rRNA amplicon surveys, which are not sufficiently resolved to inform biogeochemical models. To survey the metabolic potential and gene expression underpinning carbon and nitrogen biogeochemical cycling in river sediments, we collected an integrated dataset of over 30 metagenomes, metaproteomes, and paired metabolomes. We reconstructed over 500 microbial metagenome assembled genomes (MAGs), which we dereplicated into 55 unique genomes spanning 12 bacterial and archaeal phyla. We also reconstructed 2482 viral genomic contigs, which were dereplicated into 111 viral MAGs >10kb in size. As a result of integrating gene expression data with geochemical and metabolite data, we created a conceptual model that uncovers new roles for microorganisms in organic matter decomposition, carbon sequestration, nitrogen mineralization, nitrification, and denitrification. Integrated through shared resource pools of ammonium, carbon dioxide, and inorganic nitrogen we show how these metabolic pathways could ultimately contribute to carbon dioxide and nitrous oxide fluxes from hyporheic sediments. Further, by linking viral genomes to these active microbial hosts, we provide some of the first insights into viral modulation of river sediment carbon and nitrogen cycling. ImportanceHere we created HUM-V (Hyporheic Uncultured Microbial and Viral), an annotated microbial and viral genome catalog that captures the strain and functional diversity encoded in river sediments. Demonstrating its utility, this genomic inventory encompasses multiple representatives of the most dominant microbial and archaeal phyla reported in river sediments and provides novel viral genomes that can putatively infect these. Furthermore, we used HUM-V to recruit gene expression data to decipher the functional activities of these genomes and reconstruct their active roles in river sediment biogeochemical cycling. We show the power of genome resolved, multi-omics to uncover the organismal interactions and chemical handoffs shaping an intertwined carbon and nitrogen metabolic network and create a framework that can be extended to other river sediments. The accessible microbial and viral genomes in HUM-V will serve as a community resource to further advance more untargeted, activity-based measurements in these and related freshwater terrestrial-aquatic ecosystems.

microbiology↗

bioRxiv2021

A comprehensive urine proteome database generated from patients with various renal conditions and prostate cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers. Surprisingly, 43% (167) of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as myoglobin, serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

systems biology↗

bioRxiv2020

From plants to ants: Fungal modification of leaf lipids for nutrition and communication in the leaf-cutter ant fungal garden ecosystem

Lipids are essential to all living organisms, as an energy source, as an important cellular structural component, and as a communication tool. In this study, we used global lipidomic methods to evaluate the lipids in leaf-cutter ant fungal gardens. Leaf-cutter ants and their coevolved fungal cultivar, Leucoagaricus gongylophorus, are a model mutualistic system. The fungus enzymatically digests fresh plant material that the ants cut and deliver, converting energy and nutrients from plants, and providing them to the ants through specialized hyphal swellings called gongylidia. Using combined liquid chromatography, ion mobility spectrometry, and tandem mass spectrometry we evaluated differences between the molecular speciation of lipids in the leaf-cutter ant fungal garden ecosystem. This lipidomic study characterized leaves that are fed to the gardens, gongylidia that are produced by the fungus to feed the ants, and spatially resolved regions of the fungal garden through stages of leaf degradation. Lipids containing alpha-linolenic acid (18:3) were enriched in leaves and the top of the gardens, but not dominant in the middle or bottom regions. Gongylidia were dominated by lipids containing linoleic acid (18:2). To evaluate the communicative potential of the lipids in fungal gardens we conducted a behavioral experiment that showed Atta leaf-cutter ants responded differently to 18:3 and 18:2 fatty acids, with aggression towards 18:3 and attraction for 18:2. This work demonstrates the role of lipids in both the transfer of energy and as an inter-kingdom communication tool in leaf-cutter ant fungal gardens. ImportanceIn this work we examined the role of lipids in the mutualism between leaf-cutter ants and fungus. These ants cut fresh leaf material, which they provide to their fungal cultivar, that converts energy and nutrients from the plants and provides it to the ants in specialized hyphal swellings called gongylidia. This work constitutes the first example of a global lipidomics study of a symbiotic system and provides insights as to how the fungus modifies plant lipids into a usable source for the ants. Through a behavioral experiment, this work also demonstrates how lipids can be used as an inter-kingdom communication tool, in this case an attractant, rather than as a repellant, which is more often seen.

systems biology↗

bioRxiv2020

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS.

Gas chromatography-mass spectrometry (GC-MS) represents an analytical technique with significant practical societal impact. Spectral deconvolution is an essential step for interpreting GC-MS data. No public GC-MS repositories that also enable repository-scale analysis exist, in part because deconvolution requires significant user input. We therefore engineered a scalable machine learning workflow for the Global Natural Product Social Molecular Networking (GNPS) analysis platform to enable the mass spectrometry community to store, process, share, annotate, compare, and perform molecular networking of GC-MS data. The workflow performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization, using a Fast Fourier Transform-based strategy to overcome scalability limitations. We introduce a "balance score" that quantifies the reproducibility of fragmentation patterns across all samples. We demonstrate the utility of the platform with breathomics analysis applied to the early detection of oesophago-gastric cancer, and by creating the first molecular spatial map of the human volatilome.

bioinformatics↗

bioRxiv2019

Sporadic ERK pulses drive non-genetic resistance in drug-adapted BRAFV600E melanoma cells

Anti-cancer drugs commonly target signal transduction proteins activated by mutation. In patients with BRAFV600E melanoma, small molecule RAF and MEK kinase inhibitors cause dramatic but often transient tumor regression. Emerging evidence suggests that cancer cells adapting by non-genetic mechanisms constitute a reservoir for the development of drug-resistant tumors. Here, we show that few hours after exposure to RAF/MEK inhibitors, BRAFV600E melanomas undergo adaptive changes involving disruption of negative feedback and sporadic pulsatile reactivation of the MAPK pathway, so that MAPK activity is transiently high enough in some cells to drive proliferation. Quantitative proteomics and computational modeling show that pulsatile MAPK reactivation is possible due to the co-existence in cells of two MAPK cascades: one driven by BRAFV600E that is drug-sensitive and a second driven by receptors that is drug-resistant. Paradoxically, this may account both for the frequent emergence of drug resistance and for the tolerability of RAF/MEK therapy in patients.

cancer biology↗

bioRxiv2019

Broad substrate-specific phosphorylation events are associated with the initial stage of plant cell wall recognition in Neurospora crassa

Fungal plant cell wall degradation processes are governed by complex regulatory mechanisms, allowing the organisms to adapt their metabolic program with high specificity to the available substrates. While the uptake of representative plant cell wall mono- and disaccharides is known to induce specific transcriptional and translational responses, the processes related to early signal reception and transduction remain largely unkown. A fast and reversible way of signal transmission are post-translational protein modifications, such as phosphorylations, which could initiate rapid adaptations of the fungal metabolism to a new condition. To elucidate how changes in the initial substrate recognition phase of Neurospora crassa affect the global phosphorylation pattern, phospho-proteomics was performed after a short (2 minutes) induction period with several plant cell wall-related mono- and disaccharides. The MS/MS-based peptide analysis revealed large-scale substrate-specific protein phosphorylation and de-phosphorylations. Using the proteins identified by MS/MS, a protein-protein-interaction (PPI) network was constructed. The variance in phosphorylation of a large number of kinases, phosphatases and transcription factors indicate the participation of many known signaling pathways, including circadian responses, two-component regulatory systems, MAP kinases as well as the cAMP-dependent and heterotrimeric G-protein pathways. Adenylate cyclase, a key component of the cAMP pathway, was identified as a potential hub for carbon source-specific differential protein interactions. In addition, four phosphorylated F-Box proteins were identified, two of which, Fbx-19 and Fbx-22, were found to be involved in carbon catabolite repression responses. Overall, these results provide unprecedented and detailed insights into a so far less well known stage of the fungal response to environmental cues and allow to better elucidate the molecular mechanisms of sensory perception and signal transduction during plant cell wall degradation.

molecular biology↗

bioRxiv2018

Integrated systems biology and imaging of the smallest free-living eukaryote Ostreococcus tauri

Ostreococcus tauri is an ancient phototrophic microalgae that possesses favorable genetic and cellular characteristics for reductionist studies probing biosystem design and dynamics. Here multimodal bioimaging and multi-omics techniques were combined to interrogate O. tauri cellular changes in response to variations in bioavailable nitrogen and carbon ratios. Confocal microscopy, stimulated Raman scattering, and cryo-soft x-ray tomography revealed whole cell ultrastructural dynamics and composition while proteomic and lipidomic profiling captured changes at the molecular and macromolecular scale.\n\nDespite several energy dense long-chain triacylglycerol lipids showing more than 40-fold higher abundance under N deprivation, only a few proteins directly associated with lipid biogenesis showed significant expression changes. However, the entire pathway for starch granule biosynthesis was highly upregulated suggesting much of the cellular energy is preferentially directed towards starch over lipid accumulation. Additionally, three of the five most downregulated and five of the ten most upregulated proteins during severe nitrogen depletion were unnamed protein products that warrant additional biochemical analysis and functional annotation to control carbon transformation dynamics in this smallest eukaryote.

systems biology↗

bioRxiv2018

Multi omics comparison reveals metabolome biochemistry, not microbiome composition or gene expression, corresponds to elevated biogeochemical function in the hyporheic zone

Biogeochemical hotspots are pervasive at terrestrial-aquatic interfaces, particularly within groundwater-surface water mixing zones (hyporheic zones), and they are critical to understanding spatiotemporal variation in biogeochemical cycling. Here, we use multi omic comparisons of hotspots to low-activity sediments to gain mechanistic insight into hyporheic zone organic matter processing. We hypothesized that microbiome structure and function, as described by metagenomics and metaproteomics, would distinguish hotspots from low-activity sediments through a shift towards carbohydrate-utilizing metabolic pathways and elucidate discrete mechanisms governing organic matter processing in each location. We also expected these differences to be reflected in the metabolome, whereby hotspot carbon (C) pools and metabolite transformations therein would be enriched in sugar-associated compounds. In contrast to expectations, we found pronounced phenotypic plasticity in the hyporheic zone microbiome that was denoted by similar microbiome structure, functional potential, and expression across sediments with dissimilar metabolic rates. Instead, diverse nitrogenous metabolites and biochemical transformations characterized hotspots. Metabolomes also corresponded more strongly to aerobic metabolism than bulk C content only (explaining 67% vs. 42% of variation), and bulk C did not improve statistical models based on metabolome composition alone. These results point to organic nitrogen as a significant regulatory factor influencing hyporheic zone organic matter processing. Based on our findings, we propose incorporating knowledge of metabolic pathways associated with different chemical fractions of C pools into ecosystem models will enhance prediction accuracy.

molecular biology↗