Biology subjects

Figueroa, J. L.

Publications and source records attributed to Figueroa, J. L..

6 recordsLinked to original sources

bioRxiv2024

Resolving and Quantifying Viral-Like Particles via Blind Deconvolution

Viruses represent the most numerous biological entities on Earth; but the direct quantification of viruses within ecosystems reminds an ongoing challenge. The classical method of epifluorescence microscopy (EFM) reminds the gold standard measurement of viral-like particles (VLPs) within ecosystems. Quantifying VLPs in epifluorescence microscopy is burdened by ongoing challenges that include manual human counting, an absence of accurate morphological sizing, and the a range of viral sizes (20-300 nm) falling below the diffraction limit of light microscopy. Here, a proof-of-concept computer vision framework for the automated enumeration and sizing of viral-like particles is presented, known as EpiVirQuant. A novel tunable pointspread function is introduced which allows for a dynamic blind deconvolution. Final enumeration by EpiVirQuant was directly compared to manual human counting which yielded 18% more VLPs identified. EpiVirQuant quantified average VLP size of 179.5 nm, which is consistent with median size of VLPs in nature of of _160 nm. Runtime ranged from 60-80 seconds-perimage depending on parameter selection. This provides a viable proof-of-concept cost-effective solution for the enumeration and large-scale morphological analysis of VLPs.

bioinformatics↗

bioRxiv2024

NFixDB (Nitrogen Fixation DataBase) - A Comprehensive Integrated Database for Robust 'Omics Analysis of Diazotrophs

Biological nitrogen fixation is a fundamental biogeochemical process that transforms that provides fixed biologically available nitrogen by diazotrophic microbes. Diazotrophs anaerobically fix nitrogen using the nitrogenase enzyme which has three different gene clusters: 1) molybdenum nitrogenase (nifDHK) is the most abundant, followed by its alternatives 2) vanadium nitrogenase (vnfDHK), and 3) iron nitrogenase (anfDHK). Multiple databases have been constructed as resources for diazotrophic omics analysis; however, an integrated database based on whole genome references does not exist. Here, we present NFixDB (Nitrogen Fixation DataBase), a comprehensive integrated whole genome based database for diazotrophs, which includes all nitrogenases (nifDHK, vnfDHK, anfDHK) and nitrogenase-like enzymes (e.g., nflDH) linked to ribosomal operons (16S-5.8S-23S). NFixDB was computed using Hidden Markov Models (HMMs) against the entire whole genome based Genome Taxonomy Database (GTDB R214), providing searchable reference HMMs for all nitrogenase and nitrogenase-like genes, complete ribosomal operons, both GTDB and NCBI/RefSeq taxonomy, and an SQL database for querying matches. We compared NFixDB to nifH databases from Buckley, Zehr, Mise, and FunGene finding extensive evidence of nifH, in addition to vnfH and nflH. NFixDB contains more than 4,000 verified nifHDK sequences contained on 50 unique phyla of bacteria and archaea. NFixDB offers the first comprehensive nitrogenase database available to researchers.

bioinformatics↗

bioRxiv2024

Copper drives remodeling of metabolic state and progression of clear cell renal cell carcinoma

Copper (Cu) is an essential trace element required for mitochondrial respiration. Late-stage clear cell renal cell carcinoma (ccRCC) accumulates Cu and allocates it to mitochondrial cytochrome c oxidase. We show that Cu drives coordinated metabolic remodeling of bioenergy, biosynthesis and redox homeostasis, promoting tumor growth and progression of ccRCC. Specifically, Cu induces TCA cycle-dependent oxidation of glucose and its utilization for glutathione biosynthesis to protect against H2O2 generated during mitochondrial respiration, therefore coordinating bioenergy production with redox protection. scRNA-seq determined that ccRCC progression involves increased expression of subunits of respiratory complexes, genes in glutathione and Cu metabolism, and NRF2 targets, alongside a decrease in HIF activity, a hallmark of ccRCC. Spatial transcriptomics identified that proliferating cancer cells are embedded in clusters of cells with oxidative metabolism supporting effects of metabolic states on ccRCC progression. Our work establishes novel vulnerabilities with potential for therapeutic interventions in ccRCC. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/575895v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@14e1b89org.highwire.dtl.DTLVardef@f1c83forg.highwire.dtl.DTLVardef@191aff8org.highwire.dtl.DTLVardef@1b7ccd1_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIAccumulation of copper is associated with progression and relapse of ccRCC and drives tumor growth. C_LIO_LICu accumulation and allocation to cytochrome c oxidase (CuCOX) remodels metabolism coupling energy production and nucleotide biosynthesis with maintenance of redox homeostasis. C_LIO_LICu induces oxidative phosphorylation via alterations in the mitochondrial proteome and lipidome necessary for the formation of the respiratory supercomplexes. C_LIO_LICu stimulates glutathione biosynthesis and glutathione derived specifically from glucose is necessary for survival of CuHi cells. Biosynthesis of glucose-derived glutathione requires activity of glutamyl pyruvate transaminase 2, entry of glucose-derived pyruvate to mitochondria via alanine, and the glutamate exporter, SLC25A22. Glutathione derived from glucose maintains redox homeostasis in Cu-treated cells, reducing Cu-H2O2 Fenton-like reaction mediated cell death. C_LIO_LIProgression of human ccRCC is associated with gene expression signature characterized by induction of ETC/OxPhos/GSH/Cu-related genes and decrease in HIF/glycolytic genes in subpopulations of cancer cells. Enhanced, concordant expression of genes related to ETC/OxPhos, GSH, and Cu characterizes metabolically active subpopulations of ccRCC cells in regions adjacent to proliferative subpopulations of ccRCC cells, implicating oxidative metabolism in supporting tumor growth. C_LI

cancer biology↗

bioRxiv2023

Utilization of a Histoplasma capsulatum zinc reporter reveals the complexities of fungal sensing of metal deprivation

Histoplasma capsulatum is a dimorphic fungal pathogen acquired via inhalation of soil-resident spores. Upon exposure to mammalian body temperatures, these fungal elements transform into yeasts that reside primarily within phagocytes. Macrophages (M{Phi}) provide a permissive environment for fungal replication until T cell-dependent immunity is engaged. M{Phi} activated by granulocyte-M{Phi} colony stimulating factor (GM-CSF) induce metallothioneins (MTs) that bind zinc (Zn) and deprive yeast cells of labile Zn, thereby disabling fungal growth. Prior work demonstrated that the high affinity zinc importer, ZRT2, was important for fungal survival in vivo. Hence, we constructed a yeast cell reporter strain that expresses green fluorescent protein (GFP) under the control of this importer. This reporter accurately responds to medium devoid of Zn. ZRT2 expression increased ([~]5-fold) in GM-CSF, but not interferon-{gamma}, stimulated M{Phi}. To examine the in vivo response, we infected mice with reporter yeasts and assessed ZRT2 expression at 0-, 3-, 7-, and 14-days post-infection (dpi). ZRT2 expression minimally increased at 3-dpi and peaked on 7-dpi, corresponding with onset of adaptive immunity. We discovered that the major phagocyte populations that restrict Zn to the fungus are interstitial M{Phi} and exudate M{Phi}. Neutralizing GM-CSF blunted control of infection but unexpectedly increased ZRT2 expression. This increase was dependent on another cytokine that activates M{Phi} to control H. capsulatum replication, M-CSF. These findings illustrate the reporters ability to sense Zn in vitro and in vivo and correlate ZRT2 activity with GM-CSF and M-CSF activation of M{Phi}. ImportancePhagocytes use an arsenal of defenses to control replication of Histoplasma yeasts, one of which is limitation of trace metals. On the other hand, H. capsulatum combats metal restriction by upregulating metal importers such as the Zn importer ZRT2. This transporter contributes to H. capsulatum pathogenesis upon activation of adaptive immunity. We constructed a fluorescent ZRT2 reporter to probe H. capsulatum Zn sensing during infection and exposed a role for M-CSF activation of macrophages when GM-CSF is absent. These data highlight the ways in which fungal pathogens sense metal deprivation in vivo and reveal the potential of metal-sensing reporters. The work adds a new dimension to studying how intracellular pathogens sense and respond to the changing environments of the host.

microbiology↗

bioRxiv2023

MetaCerberus: distributed highly parallelized scalable HMM-based implementation for robust functional annotation across the tree of life

SummaryMetaCerberus is an exclusive HMM/HMMER-based tool that is massively parallel, on low memory, and provides rapid scalable annotation for functional gene inference across genomes to metacommunities. It provides robust enumeration of functional genes and pathways across many current public databases including KEGG (KO), COGs, CAZy, FOAM, and viral specific databases (i.e., VOGs and PHROGs). In a direct comparison, MetaCerberus was twice as fast as EggNOG-Mapper, and produced better annotation of viruses, phages, and archaeal viruses than DRAM, PROKKA, or InterProScan. MetaCerberus annotates more KOs across domains when compared to DRAM, with a 186x smaller database and a third less memory. MetaCerberus is fully integrated with differential statistical tools (i.e., DESeq2 and edgeR), pathway enrichment (GAGE R), and Pathview R for quantitative elucidation of metabolic pathways. MetaCerberus implements the key to unlocking the biosphere across the tree of life at scale. Availability and implementationMetaCerberus is written in Python and distributed under a BSD-3 license. The source code of MetaCerberus is freely available at https://github.com/raw-lab/metacerberus. Written in python 3 for both Linux and Mac OS X. MetaCerberus can also be easily installed using mamba create -n metacerberus -c bioconda -c conda-forge metacerberus

bioinformatics↗

bioRxiv2022

MerCat2: a versatile k-mer counter and diversity estimator for database-independent property analysis obtained from omics data

SummaryMerCat2 ("Mer - Catenate2") is a versatile, parallel, scalable and modular property software package for robustly analyzing features in omics data. Using massively parallel sequencing raw reads, assembled contigs, and protein sequences from any platform as input, MerCat2 performs k-mer counting of any length k, resulting in feature abundance counts tables, quality control reports, protein feature metrics, ecological diversity metrics, and graphical representation (i.e., PCA). MerCat2 allows for direct analysis of data properties in a database-independent manner that initializes all data, which other profilers and assembly-based methods cannot perform. MerCat2 represents an integrated tool to illuminate omics data within a sample for rapid cross-examination and comparisons. Availability and implementationMerCat2 is written in Python and distributed under a BSD-3 license. The source code of MerCat2 is freely available at https://github.com/raw-lab/mercat2. MerCat2 is compatible with Python 3 on Mac OS X and Linux. MerCat2 can also be easily installed using bioconda: conda install MerCat2. ContactRichard Allen White III, UNC Charlotte, rwhit101@uncc.edu Supplementary informationSupplementary data are available online.

bioinformatics↗