Biology subjects

Petras, D.

Publications and source records attributed to Petras, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

High Resolution Biological and Physical Sampling Reveals Expression of Domoic Acid Biosynthetic Genes at Frontal Zones

Ocean microbes are the foundation of marine food webs, regulating carbon cycling and ecosystem dynamics. How they proliferate, die, move, and interact is regulated by physical, chemical, and biological factors that are dynamic and challenging to quantify in the natural environment. A significant limitation in many marine field studies is the inability to continuously sample the ever-changing ocean environment over space and time. In this study, we integrated spatiotemporal and multi-omic sample collection in an intensive sampling effort of phytoplankton ecology in Monterey Bay, California during the spring of 2021. Sampling methods coupled: (1) manual shipboard CTD sampling, (2) autonomous sampling using a Long-Range Autonomous Underwater Vehicle (LRAUV) equipped with an Environmental Sampling Processor (ESP), and (3) high-resolution physical measurements by an autonomous vertical profiler (Wirewalker). Sampling occurred as upwelling waned alongside declining domoic acid (DA) and low abundances of toxigenic Pseudo-nitzschia. Conditions needed to spark a widespread and toxic Pseudo-nitzschia bloom were absent, yet low-level DA was driven by similar mechanisms to those causing elevated DA. Three DA biosynthetic intermediate molecules were reported in the environment for the first time. Both shipboard and ESP sampling approaches identified DA biosynthetic gene expression at frontal zones. DA and expression of dabA, the gene encoding the first committed step of DA biosynthesis, were higher in association with recently upwelled water that supplied nutrients for growth and DA biosynthesis. Detection of subtle variations in dab gene expression in response to environmental variation provide a window into the ecological dynamics underpinning major toxic events. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/562961v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@1c1f554org.highwire.dtl.DTLVardef@d16b02org.highwire.dtl.DTLVardef@c856e1org.highwire.dtl.DTLVardef@bfd248_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2022

A Universal Language for Finding Mass Spectrometry Data Patterns

Even though raw mass spectrometry data is information rich, the vast majority of the data is underutilized. The ability to interrogate these rich datasets is handicapped by the limited capability and flexibility of existing software. We introduce the Mass Spec Query Language (MassQL) that addresses these issues by enabling an expressive set of mass spectrometry patterns to be queried directly from raw data. MassQL is an open-source mass spectrometry query language for flexible and mass spectrometer manufacturer-independent mining of MS data. We envision the flexibility, scalability, and ease of use of MassQL will empower the mass spectrometry community to take fuller advantage of their mass spectrometry data and accelerate discoveries.

bioinformatics↗

bioRxiv2022

Open Access Repository-Scale Propagated Nearest Neighbor Suspect Spectral Library for Untargeted Metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of public MS/MS spectra. Annotations were propagated based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimers brain phenotype. The nearest neighbor suspect spectral library is openly available through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

bioinformatics↗

bioRxiv2022

Taxonomic and functional diversity of aquatic heterotrophs is sustained by dissolved organic matter chemodiversity

Dissolved organic matter (DOM) is ubiquitous in aquatic ecosystems and fundamental for planetary processes and ecosystem functioning. While the link between microbial community composition and heterotrophic utilization of DOM has been recognized, the full diversity of organic compounds, their bioavailability, degradability and specific influences on the diversity and function of heterotrophs are still not clear. Here we experimentally investigate heterotrophic bacteria in thirty-three freshwater model communities. We identified 34 different heterotrophs growing in ambient lake DOM with taxonomic affiliations matching abundant freshwater bacterioplankton. We further describe 25 different heterotrophs growing in the phycosphere of M. Aeruginosa and 6 heterotrophs growing on the DOM produced by M. Aeruginosa with taxonomic affiliation in accord to phycosphere heterotrophs. In our experiment we observed that heterotrophs that live in the phycosphere remove more dissolved organic carbon than abundant freshwater heterotrophs. Moreover, phycosphere heterotrophs have bigger genomes than abundant lake bacteria. Altogether of the 4224 chemical features that were resolved by LC-MS, only 1229 were seen in all three treatments. None of the common/shared compounds were removed across all the model communities, suggesting contrasting niches of the studied taxa. Altogether our study highlights how each model community, with its unique taxonomic assemblages and organotroph functioning is upkept by the chemodiversity of DOM.

ecology↗

bioRxiv2022

Spatial Venomics - Cobra Venom System Reveals Spatial Differentiation of Snake Toxins by Mass Spectrometry Imaging

Among venomous animals, toxic secretions have evolved as biochemical weapons associated with various highly specialized delivery systems on many occasions. Despite extensive research, there is still limited knowledge of the functional biology of most animal toxins, including their venom production and storage, as well as the morphological structures within sophisticated venom producing tissues that might underpin venom modulation. Here we report on the spatial exploration of a snake venom gland system by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), in combination with standard proteotranscriptomic approaches, to enable in situ toxin mapping in spatial intensity maps across a venom gland sourced from the Egyptian cobra (Naja haje). MALDI-MSI toxin visualization on the elapid venom gland reveals high spatial heterogeneity of different toxin classes at the proteoform level, which may be the result of physiological constraints on venom production and/or storage that reflects the potential for venom modulation under diverse stimuli.

biochemistry↗

bioRxiv2021

Native Metabolomics Identifies the Rivulariapeptolide Family of Protease Inhibitors

The identity and biological activity of most metabolites still remain unknown. A key bottleneck in the full exploration of this tremendous source of new structures and pharmaceutical activities is the compound purification needed for bioactivity assignments of individual compounds and downstream structure elucidation. To enable bioactivity-focused compound identification from complex mixtures, we developed a scalable native metabolomics approach that integrates non-targeted liquid chromatography tandem mass spectrometry, and simultaneous detection of protein binding via native mass spectrometry. While screening for new protease inhibitors from an environmental cyanobacteria community, native metabolomics revealed 30 cyclodepsipeptides as chymotrypsin binders. Mass spectrometry-guided purification then allowed for the full structure elucidation of four new specialized metabolites via tandem mass spectrometry, chemical derivatization, and nuclear magnetic resonance spectroscopy. Together with the evaluation of biological activities, our results identified the rivulariapeptolides as a family of serine protease inhibitors with nanomolar potency, highlighting native metabolomics as promising approach for drug discovery, chemical ecology, and chemical biology studies.

systems biology↗

bioRxiv2021

Mutualistic interactions between B. subtilis and seeds dictate plant development

A tightly coordinated developmental program controls precise genetic and metabolic reprogramming that dictates efficient transition of the seeds from dormancy to metabolically active seedlings. Beneficial microbes are known to stimulate the germination of the seeds or adaptation of the seedlings; however, investigations of exact mechanisms mediating these interactions and the resulting physiological responses of the plants are only beginning. Bacillus subtilis is commonly detected in the plant holobiont and belongs to the group of microbes that provide multifaceted contribution to the health of the plants. The present study demonstrated that B. subtilis triggered genetic and physiological responses in the seeds that determined subsequent metabolic and developmental status of adult plants. Chemically diverse extracellular matrix of Bacillus was demonstrated to structurally cooperate in bacterial colonization of the seed storage tissues. Additionally, an amyloid protein and fengycin, which are two components of the extracellular matrix, targeted the oil bodies of the seed endosperm, provoking changes in lipid metabolism or accumulation of glutathione-related molecules that stimulated two different plant growth programs: the development of seed radicles or overgrowth and immunization of adult plants. We propose this mutualistic interaction is conserved in Bacilli and plant seeds containing storage oil bodies.

microbiology↗

bioRxiv2021

Multi-omics profiling of Earth's biomes reveals that microbial and metabolite composition are shaped by the environment

As our understanding of the structure and diversity of the microbial world grows, interpreting its function is of critical interest for understanding and managing the many systems microbes influence. Despite advances in sequencing, lack of standardization challenges comparisons among studies that could provide insight into the structure and function of microbial communities across multiple habitats on a planetary scale. Technical variation among distinct studies without proper standardization of approaches prevents robust meta-analysis. Here, we present a multi-omics, meta-analysis of a novel, diverse set of microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry), centering our description on relationships and co-occurrences of microbially-related metabolites and microbial taxa across environments. Standardized protocols and analytical methods for characterizing microbial communities, including assessment of molecular diversity using untargeted metabolomics, facilitate identification of shared microbial and metabolite features, permitting us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of a community resource that will become more valuable with time. To provide examples of applying this database, we outline important ecological questions that can be addressed, and test the hypotheses that every microbe and metabolite is everywhere, but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment. The relative abundances of microbially-related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner, and highlight the power of certain chemistry - in particular terpenoids - in distinguishing Earths environments.

ecology↗

bioRxiv2021

GNPS Dashboard: Collaborative Analysis of Mass Spectrometry Data in the Web Browser

Access to web-based platforms has enabled scientists to perform research remotely. A critical aspect of mass spectrometry data analysis is the inspection, analysis, and visualization of the raw data to validate data quality and confirm statistical observations. We developed the GNPS Dashboard, a web-based data visualization tool, to facilitate synchronous collaborative inspection, visualization, and analysis of private and public mass spectrometry data remotely.

bioinformatics↗

bioRxiv2021

Chemical interplay and complementary adaptative strategies toggle bacterial antagonism and co-existence

Bacterial communities are in a continuous adaptive and evolutionary race for survival. A myriad of molecules that kill, defend, or mediate communication between bacterial cells of different lineages shape the final structure of the microbial community. In this work we expand our knowledge on the chemical interplay and specific mutations that modulate the transition from antagonism to co-existence between two plant-beneficial bacteria, Pseudomonas chlororaphis PCL1606 and Bacillus amyloliquefaciens FZB42. We reveal that the bacteriostatic activity of bacillaene produced by Bacillus relies on an interaction with the protein elongation factor FusA and how mutations in this protein lead to tolerance to bacillaene and other protein translation inhibitors. Additionally, we describe how the unspecific tolerance to antimicrobials associated with mutations in the glycerol kinase GlpK is provoked mainly by a decrease of Bacillus cell membrane permeability among other pleiotropic cellular responses. We conclude that nutrient specialization and mutations in basic biological functions are bacterial evolutive and adaptive strategies that lead to the coexistence of two primary competitive bacterial species rather than their mutual eradication.

microbiology↗

bioRxiv2020

The ant fungus garden acts as an external digestive system

Most animals digest their food within their own bodies, but some do not. Many species of ants grow fungus gardens that pre-digest food as an essential step of the ants nutrient uptake. To better understand this digestion process, we generated a 3D molecular map of an Atta texana fungus garden, revealing chemical modifications mediated by the fungus garden as plant material passes through.

systems biology↗

bioRxiv2020

Siderophore-mediated zinc acquisition enhances enterobacterial colonization of the inflamed gut.

Zinc is an essential cofactor for bacterial metabolism, and many Enterobacteriaceae express the zinc transporters ZnuABC and ZupT to acquire this metal in the host. Unexpectedly, the probiotic bacterium Escherichia coli Nissle 1917 exhibited appreciable growth in zinc-limited media even when these transporters were deleted. By utilizing in vitro and in vivo studies, as well as native spray metal infusion mass spectrometry and ion identity molecular networking, we discovered that Nissle utilizes yersiniabactin as a zincophore. Indeed, yersiniabactin enables Nissle to scavenge zinc in zinc-limited media, to resist calprotectin-mediated zinc sequestration, and to thrive in the inflamed gut. Moreover, we discovered that yersiniabactins affinity for iron or zinc changes in a pH-dependent manner, with higher affinity for zinc as the pH increased. Altogether, we demonstrate that siderophore metal affinity can be influenced by the local environment and reveal a mechanism of zinc acquisition available to many commensal and pathogenic Enterobacteriaceae.

microbiology↗

bioRxiv2020

Ion Identity Molecular Networking in the GNPS Environment

Molecular networking connects tandem mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. To connect ion species of the same molecule, we developed Ion Identity Molecular Networking. These new relationships improve network connectivity, are shown to reveal novel ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral libraries.

bioinformatics↗

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

ZODIAC: database-independent molecular formula annotation using Gibbs sampling reveals unknown small molecules

1The confident high-throughput identification of small molecules remains one of the most challenging tasks in mass spectrometry-based metabolomics. SIRIUS has become a powerful tool for the interpretation of tandem mass spectra, and shows outstanding performance for identifying the molecular formula of a query compound, being the first step of structure identification. Nevertheless, the identification of both molecular formulas for large compounds above 500 Daltons and novel molecular formulas remains highly challenging. Here, we present ZODIAC, a network-based algorithm for the de novo estimation of molecular formulas. ZODIAC reranks SIRIUS molecular formula candidates, combining fragmentation tree computation with Bayesian statistics using Gibbs sampling. Through careful algorithm engineering, ZODIACs Gibbs sampling is very swift in practice. ZODIAC decreases incorrect annotations 16.2-fold on a challenging plant extract dataset with most compounds above 700 Dalton; we then show improvements on four additional, diverse datasets. Our analysis led to the discovery of compounds with novel molecular formulas such as C24H47BrNO8P which, as of today, is not present in any publicly available molecular structure databases.

bioinformatics↗

bioRxiv2019

Native Electrospray-based Metabolomics Enables the Detection of Metal-binding Compounds

Metals are essential for the molecular machineries of life, and microbes have evolved a variety of small molecules to acquire, compete for, and utilize metals. Systematic methods for the discovery of metal-small molecule complexes from biological samples are limited. Here we describe a two-step native electrospray ionization mass spectrometry method, in which double-barrel post-column metal-infusion and pH adjustment is combined with ion identity molecular networking, a rule-based informatics workflow. This method can be used to identify metal-binding compounds in complex samples based on defined mass (m/z) offsets of ion features with the same chromatographic profiles. As this native metal metabolomics approach can be easily implemented on any liquid chromatography-based mass spectrometry system, this method has the potential to become a key strategy for elucidating and understanding the role of metal-binding molecules in biology.

biochemistry↗

bioRxiv2019

Feature-based Molecular Networking in the GNPS Analysis Environment

Molecular networking has become a key method used to visualize and annotate the chemical space in non-targeted mass spectrometry-based experiments. However, distinguishing isomeric compounds and quantitative interpretation are currently limited. Therefore, we created Feature-based Molecular Networking (FBMN) as a new analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure. FBMN leverages feature detection and alignment tools to enhance quantitative analyses and isomer distinction, including from ion-mobility spectrometry experiments, in molecular networks.

bioinformatics↗

bioRxiv2019

Repository-scale Co- and Re-analysis of Tandem Mass Spectrometry Data

Metabolomics data are difficult to find and reuse, even in public repositories. We, therefore, developed the Reanalysis of Data User (ReDU) interface (https://redu.ucsd.edu/), a community- and data-driven approach that solves this problem at the repository scale. ReDU enables public data discovery and co- or re-analysis via uniformly formatted, publicly available MS/MS data and metadata in the Global Natural Product Social Molecular Networking Platform (GNPS), consistent with findable, accessible, interoperable, and reusable (FAIR) principles.1

bioinformatics↗