SEARCH · Engineering Papers

Results for “cluster characterization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Scintillator-based Timepix3 detector for neutron spin-echo techniques using intensity modulation

A scintillator-based Timepix3 (TPX3) detector was developed to resolve the high-frequency modulation of a neutron beam in both spatial and temporal domains, as required for neutron spin-echo experiments. In this system, light from a scintillator is manipulated with an optical lens and is intensified using an image intensifier, making it detectable with the TPX3 chip. Two different scintillators, namely, 6 LiF:ZnS(Ag) and 6 LiI:Eu, were investigated to achieve the high resolution needed for spin-echo modulated small-angle neutron scattering (SEMSANS) and modulation of intensity with zero effort (MIEZE). The methodology for conducting event-mode analysis is described, including the optimization of clustering parameters for both scintillators. The detector with both scintillators was characterized with respect to detection efficiency, spatial resolution, count rate, uniformity, and γ-sensitivity. The 6 LiF:ZnS(Ag) scintillator-based detector achieved a spatial resolution of 200 μm and a count rate capability of 1.1 × 10 5 cps, while the 6 LiI:Eu scintillator-based detector demonstrated a spatial resolution of 250 μm and a count rate capability exceeding 2.9 × 10 5 cps. Furthermore, high-frequency intensity modulations in both spatial and temporal domains were successfully observed, confirming the suitability of this detector for SEMSANS and MIEZE techniques, respectively.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

One Galaxy Sample to Rule Them All: Halo Occupation Distribution Modeling of DES Year 3 Source Galaxies

Abstract For the joint analysis of second-order weak-lensing and galaxy clustering statistics, so-called 3 × 2 analyses, the selection and characterization of optimal galaxy samples is a major area of research. One promising choice is to use the same galaxy sample as lenses and sources, which reduces the systematics parameter space that describes the uncertainties related to galaxy samples. Such a “lens-equal-source” analysis significantly improves the self-calibration of photo- z systematics, leading to improved cosmological constraints. With the aim of enabling a lens-equal-source analysis on small scales, we investigate the halo–galaxy connection of DES Year 3 source galaxies. We develop a technique to construct mock source galaxy populations by matching COSMOS/UltraVISTA photometry to U niverse M achine galaxies. These mocks predict a source halo occupation distribution (HOD) that exhibits significant redshift evolution, nontrivial central incompleteness, and galaxy assembly bias. We produce multiple realizations of mock source galaxies drawn from the U niverse M achine posterior, with added uncertainties in the measured Dark Energy Survey photometry and galaxy shapes. We fit a modified HOD formalism to these realizations to produce priors on the galaxy–halo connection for cosmological analyses. We additionally train an emulator that predicts this HOD to ∼2% accuracy from redshift z = 0.1−1.3 that models the dependence of this HOD on (1) observational uncertainties in galaxy size and photometry and (2) uncertainties in the U niverse M achine predictions.

Salcedo, Andrés N. (ORCID:000000031420527X)↗

DOE OSTI2023

Building Alternative Indices of Socioeconomic Status for Population Modeling in Data-Sparse Contexts (Short Paper)

Population modeling requires clear definitions of socioeconomic status (SES) to ensure overall estimate accuracy and locate potentially underserved subpopulations. This presents a challenge as SES can be measured in myriad ways and for divergent purposes, and the data required to calculate these metrics may be lacking, particularly in low and middle income countries (LMICs). To support more refined SES measurement, we explore improvements upon the Demographic and Health Survey’s (DHS) Wealth Index (DHS-WI) using alternative characterizations of SES based on multiple correspondence analysis (MCA) and hierarchical clustering. We produce the MCA-derived metrics first on a full suite of household economic, demographic, and dwelling variables, then on a reduced set of occupant-only SES characteristics. We explore the utility of these metrics relative to DHS-WI based on their ability to 1) differentiate DHS household types and 2) identify mixtures of SES levels within DHS samples and mapped at high spatial resolution. We find that our full suite MCA yields more clearly defined SES segments and that our reduced MCA delineates occupant SES most clearly, suggesting potential pathways to improve upon the DHS-WI in future population modeling efforts for LMICs.

Cunningham, Angela↗

DOE OSTI2024

Recombineering machinery to increase homology directed genome editing in thermophilic microbes

A native Type I-B and heterologous Type II Clustered Regularly-Interspaced Short Palindromic Repeat/cas systems were developed and characterize to improve the ability to engineer C. thermocellum and other thermophilic microbes. The native Type I-B system was engineered for genome editing. For the Type I-B system, an engineered strain, termed LL1586, yielded 40% genome editing efficiency at the pyrF locus. When recombineering machinery was expressed the efficiency was increased to 71%. For the Type II GeoCas9 system, 12.5% genome editing efficiency was observed. When recombineering machinery was expressed, this increased to 94%. By combining the thermophilic CRISPR system (either Type I-B or Type II) with the recombinases, a new tool was developed that allows for efficient CRISPR editing. The tools provided herein enable CRISPR technologies to better engineer C. thermocellum, including engineering C. thermocellum for both increased lignocellulose degradation and biofuel production.

Eckert, Carrie↗

DOE OSTI2024

Modulating metal-centered dimerization of a lanthanide chaperone protein for separation of light lanthanides

Elucidating details of biology’s selective uptake and trafficking of rare earth elements, particularly the lanthanides, has the potential to inspire sustainable biomolecular separations of these essential metals for myriad modern technologies. Here, we biochemically and structurally characterize Methylobacterium (Methylorubrum) extorquens LanD, a periplasmic protein from a bacterial gene cluster for lanthanide uptake. This protein provides only four ligands at its surface-exposed lanthanide-binding site, allowing for metal-centered protein dimerization that favors the largest lanthanide, La III . However, the monomer prefers Nd III and Sm III , which are disfavored lanthanides for cellular utilization. Structure-guided mutagenesis of a metal-ligand and an outer-sphere residue weakens metal binding to the LanD monomer and enhances dimerization for Pr III and Nd III by 100-fold. Selective dimerization enriches high-value Pr III and Nd III relative to low-value La III and Ce III in an all-aqueous process, achieving higher separation factors than lanmodulins and comparable or better separation factors than common industrial extractants. Finally, we show that LanD interacts with lanmodulin (LanM), a previously characterized periplasmic protein that shares LanD’s preference for Nd III and Sm III . Our results suggest that LanD’s unusual metal-binding site transfers less-desirable lanthanides to LanM to siphon them away from the pathway for cytosolic import. The properties of LanD show how relatively weak chelators can achieve high selectivity, and they form the basis for the design of protein dimers for separation of adjacent lanthanide pairs and other metal ions.

lanthanide biochemistry↗

DOE OSTI2021

COOL-LAMPS. I. An Extraordinarily Bright Lensed Galaxy at Redshift 5.04

In this paper, we report the discovery of COOL J1241+2219, a strongly lensed galaxy at redshift z = 5.043 ± 0.002 with observed magnitude z AB = 20.47, lensed by a moderate-mass galaxy cluster at z = 1.001 ± 0.001. COOL J1241+2219 is the brightest lensed galaxy currently known at optical and near-infrared wavelengths at z $\gtrsim$ 5; it is ~5 times brighter than the prior record-holder lensed galaxy, and several magnitudes brighter than the brightest unlensed galaxies known at these redshifts. It was discovered as part of COOL-LAMPS, a collaboration initiated to find strongly lensed systems in recent public optical imaging data. We characterize the lensed galaxy, as well as the central galaxy of the lensing cluster using ground-based grizJH imaging and optical spectroscopy. We report model-based magnitudes, and derive stellar masses, dust content, metallicity, and star-formation rates via stellar-population synthesis modeling. Our lens mass modeling, based on ground-based imaging, implies a median source magnification of ~30, which puts the stellar mass and star-formation rate (in the youngest age bin, closest to the epoch of observation) at logM* = ${10.11}_{-0.26}^{+0.21}$ and SFR = ${27}_{-9}^{+13} M_⊙$ yr –1 , respectively. We constrain a star-formation history for COOL J1241+2219 consistent with constant star formation across ~1 Gyr of cosmic time, and that places this galaxy on the high-mass end of the star-forming main sequence. COOL J1241+2219 is two to four times more luminous than a galaxy with the characteristic UV luminosity at these redshifts. The UV continuum slope β = –2.2 ± 0.2 places this galaxy on the blue side of the observed distribution of galaxies at z = 5, although the lack of Lyα emission indicates dust sufficient to suppress this emission.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts

Abstract Infrared (IR) spectra of adsorbate vibrational modes are sensitive to adsorbate/metal interactions, accurate, and easily obtainable in-situ or operando. While they are the gold standards for characterizing single-crystals and large nanoparticles, analogous spectra for highly dispersed heterogeneous catalysts consisting of single-atoms and ultra-small clusters are lacking. Here, we combine data-based approaches with physics-driven surrogate models to generate synthetic IR spectra from first-principles. We bypass the vast combinatorial space of clusters by determining viable, low-energy structures using machine-learned Hamiltonians, genetic algorithm optimization, and grand canonical Monte Carlo calculations. We obtain first-principles vibrations on this tractable ensemble and generate single-cluster primary spectra analogous to pure component gas-phase IR spectra. With such spectra as standards, we predict cluster size distributions from computational and experimental data, demonstrated in the case of CO adsorption on Pd/CeO 2 (111) catalysts, and quantify uncertainty using Bayesian Inference. We discuss extensions for characterizing complex materials towards closing the materials gap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Statistical 3D morphology characterization of vaterite microspheres produced by engineered Escherichia coli

Hollow vaterite microspheres are important materials for biomedical applications such as drug delivery and regenerative medicine owing to their biocompatibility, high specific surface area, and ability to encapsulate a large number of bioactive molecules and compounds. We demonstrated that hollow vaterite microspheres are produced by an Escherichia coli strain engineered with a urease gene cluster from the ureolytic bacteria Sporosarcina pasteurii in the presence of bovine serum albumin. We characterized the 3D nanoscale morphology of five biogenic hollow vaterite microspheres using 3D high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) tomography. Using automated high-throughput HAADF-STEM imaging across several sample tilt orientations, we show that the microspheres evolved from a smaller more ellipsoidal shape to a larger more spherical shape while the internal hollow core increased in size and remained relatively spherical, indicating that the microspheres produced by this engineered strain likely do not contain the bacteria. The statistical 3D morphology information demonstrates the potential for using biogenic calcium carbonate mineralization to produce hollow vaterite microspheres with controlled morphologies.

3D morphology↗

DOE OSTI2024

Probing Basal and Prismatic Planes of Graphitic Materials for Metal Single Atom and Subnanometer Cluster Stabilization

Abstract Supported metal single atom catalysis is a dynamic research area in catalysis science combining the advantages of homogeneous and heterogeneous catalysis. Understanding the interactions between metal single atoms and the support constitutes a challenge facing the development of such catalysts, since these interactions are essential in optimizing the catalytic performance. For conventional carbon supports, two types of surfaces can contribute to single atom stabilization: the basal planes and the prismatic surface; both of which can be decorated by defects and surface oxygen groups. To date, most studies on carbon‐supported single atom catalysts focused on nitrogen‐doped carbons, which, unlike classic carbon materials, have a fairly well‐defined chemical environment. Herein we report the synthesis, characterization and modeling of rhodium single atom catalysts supported on carbon materials presenting distinct concentrations of surface oxygen groups and basal/prismatic surface area. The influence of these parameters on the speciation of the Rh species, their coordination and ultimately on their catalytic performance in hydrogenation and hydroformylation reactions is analyzed. The results obtained show that catalysis itself is an interesting tool for the fine characterization of these materials, for which the detection of small quantities of metal clusters remains a challenge, even when combining several cutting‐edge analytical methods.

Vidal, Mathieu↗

DOE OSTI2022

Filament Formation in TaO x Thin Films for Memristor Device Application: Modeling Electron Energy Loss Spectra and Electron Transport

Abstract Although understanding filament formation in oxide‐based memristive devices by theory has emerged, there are still fundamental unanswered questions. Importantly, for practical application of thin films the material in its amorphous state is to be considered, but mostly lacking so far, and details on sub‐stoichiometry are also scarce. To gain insight into the optical and electronic properties of sub‐stoichiometric amorphous tantalum oxide (TaO x ), the electron energy loss spectrum (EELS) of model systems is characterized theoretically and electron transport characteristics are analyzed in detail. Calculated blue‐shifts by increasing sub‐stoichiometry explained the measurements, potentially suggesting estimation of oxygen vacancy concentrations through EEL spectra. Electron transport results based on TaO x material models validated by EELS measurements show that oxygen vacancy filamentary paths are initiated at low bias upon increasing sub‐stoichiometry yet noting an interplay with the local amorphous structure. Contact resistances at interfaces of the TaO x switching layer and a tantalum scavenging layer or titanium nitride electrode are quantified, indicating the possibility for either oxygen vacancy‐ or metal cluster‐based conduction mechanisms at the interface. The computational work, combined with experimental characterization for validation, provides a basis for investigating effects of sub‐stoichiometry on filament formation in TaO x thin film memristive devices.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Characterization of a novel aromatic substrate-processing microcompartment in Actinobacteria

ABSTRACT We have discovered a new cluster of genes that is found exclusively in the Actinobacteria phylum. This locus includes genes for the 2-aminophenol meta -cleavage pathway and the shell proteins of a bacterial microcompartment (BMC) and has been named aromatics (ARO) for its putative role in the breakdown of aromatic compounds. In this study, we provide details about the distribution and composition of the ARO BMC locus and conduct phylogenetic, structural, and functional analyses of the first two enzymes in the catabolic pathway: a unique 2-aminophenol dioxygenase, which is exclusively found alongside BMC shell genes in Actinobacteria, and a semialdehyde dehydrogenase, which works downstream of the dioxygenase. Genomic analysis reveals variations in the complexity of the ARO loci across different orders. Some loci are simple, containing shell proteins and enzymes for the initial steps of the catabolic pathway, while others are extensive, encompassing all the necessary genes for the complete breakdown of 2-aminophenol into pyruvate and acetyl-CoA. Furthermore, our analysis uncovers two subtypes of ARO BMC that likely degrade either 2-aminophenol or catechol, depending on the presence of a pathway-specific gene within the ARO locus. The precise precursor of 2-aminophenol, which serves as the initial substrate and/or inducer for the ARO pathway, remains unknown, as our model organism Micromonospora rosaria cannot utilize 2-aminophenol as its sole energy source. However, using enzymatic assays, we demonstrate the dioxygenase’s ability to cleave both 2-aminophenol and catechol in vitro , in collaboration with the aldehyde dehydrogenase, to facilitate the rapid conversion of these unstable and toxic intermediates. IMPORTANCE Bacterial microcompartments (BMCs) are proteinaceous organelles that are widespread among bacteria and provide a competitive advantage in specific environmental niches. Studies have shown that the genetic information necessary to form functional BMCs is encoded in loci that contain genes encoding shell proteins and the enzymatic core. This allows the bioinformatic discovery of BMCs with novel functions and expands our understanding of the metabolic diversity of BMCs. ARO loci, found only in Actinobacteria, contain genes encoding for phylogenetically remote shell proteins and homologs of the meta -cleavage degradation pathway enzymes that were shown to convert central aromatic intermediates into pyruvate and acetyl-CoA in gamma Proteobacteria. By analyzing the gene composition of ARO BMC loci and characterizing two core enzymes phylogenetically, structurally, and functionally, we provide an initial functional characterization of the ARO BMC, the most unusual BMC identified to date, distinctive among the repertoire of studied BMCs.

2-AP 1,6-dioxygenase↗

DOE OSTI2022

Controlling morphology in hybrid isotropic/patchy particle assemblies

Brownian dynamics is used to study self-assembly in a hybrid system of isotropic particles (IPs), combined with anisotropic building blocks that represent special “designer particles.” Those are modeled as spherical patchy particles (PPs) with binding only allowed between their patches and IPs. In this study, two types of PPs are considered: Octahedral PPs (Oh-PPs) and Square PPs (Sq-PPs), with octahedral and square arrangements of patches, respectively. The self-assembly is additionally facilitated by the simulated annealing procedure. Here, the resultant structures are characterized by a combination of local correlations in cubatic ordering and a symmetry-specific variation of bond orientation order parameters (SymBOPs). By varying the PP/IP size ratio, we detected a sharp crossover between two distinct morphologies in both types of systems. High symmetry phases, NaCl crystal for Oh-PP and square lattice for Sq-PP, are observed for larger size ratios. For the smaller ones, the dominant morphologies are significantly different, e.g., Oh-PPs form a compact amorphous structure with predominantly face-to-face orientation of neighboring PPs. Unusually, for a morphology without a long-range order, it is still possible to identify well organized coherent clusters of this structure, thanks to the adoption of our SymBOP-based characterization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2020

Deep learning for characterizing the self-assembly of three-dimensional colloidal systems

Creating a systematic framework to characterize the structural states of colloidal self-assembly systems is crucial for unraveling the fundamental understanding of these systems’ stochastic and non-linear behavior. The most accurate characterization methods create high-dimensional neighborhood graphs that may not provide useful information about structures unless these are well-defined reference crystalline structures. Dimensionality reduction methods are thus required to translate the neighborhood graphs into a low-dimensional space that can be easily interpreted and used to characterize non-reference structures. We investigate a framework for colloidal system state characterization that employs deep learning methods to reduce the dimensionality of neighborhood graphs. The framework next uses agglomerative hierarchical clustering techniques to partition the low-dimensional space and assign physically meaningful classifications to the resulting partitions. In this work, we first demonstrate the proposed colloidal self-assembly state characterization framework on a three-dimensional in silico system of 500 multi-flavored colloids that self-assemble under isothermal conditions. We next investigate the generalizability of the characterization framework by applying the framework to several independent self-assembly trajectories, including a three-dimensional in silico system of 2052 colloidal particles that undergo evaporation-induced self-assembly.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

Light detection and ranging (LiDAR) measurements of isolated wakes generated by wind turbines installed at an onshore wind farm are leveraged to characterize the variability of the wake mean velocity and turbulence intensity during typical operations, which encompass a breadth of atmospheric stability regimes and rotor thrust coefficients. The LiDAR measurements are clustered through the k-means algorithm, which enables identifying the most representative realizations of wind turbine wakes while avoiding the imposition of thresholds for the various wind and turbine parameters. Considering the large number of LiDAR samples collected to probe the wake velocity field, the dimensionality of the experimental dataset is reduced by projecting the LiDAR data on an intelligently truncated basis obtained with the proper orthogonal decomposition (POD). The coefficients of only five physics-informed POD modes are then injected in the k-means algorithm for clustering the LiDAR dataset. The analysis of the clustered LiDAR data and the associated supervisory control and data acquisition and meteorological data enables the study of the variability of the wake velocity deficit, wake extent, and wake-added turbulence intensity for different thrust coefficients of the turbine rotor and regimes of atmospheric stability. Furthermore, the cluster analysis of the LiDAR data allows for the identification of systematic off-design operations with a certain yaw misalignment of the turbine rotor with the mean wind direction.

17 WIND ENERGY↗

DOE OSTI2020

Roles of D1-Glu189 and D1-Glu329 in O 2 Formation by the Water-Splitting Mn 4 Ca Cluster in Photosystem II

During the catalytic step that precedes O–O bond formation in Photosystem II, a water molecule deprotonates and moves next to the water-splitting Mn 4 Ca cluster’s O5 oxo bridge. The relocated oxygen, known as O6 or Ox, may serve as a substrate, combining with O5 to form O 2 during the final step in the catalytic cycle, or may be positioned to become a substrate during the next catalytic cycle. Recent serial femtosecond X-ray crystallographic studies show that the flexibility of D1-E189 plays a critical role in facilitating the relocation of O 6 /Ox. In this study, the D1-E189G and D1-E189S mutations were characterized with FTIR difference spectroscopy. The data show that both mutations support Mn 4 Ca cluster assembly, substantially inhibit advancement beyond the S 2 state, and alter the network of H bonds that surrounds the Mn 4 Ca cluster. Previously, the D1-E189Q, D1-E189K, and D1-E189R mutations were shown to have little impact on the activity, electron transfer rates, or spectral properties of Photosystem II. A rationale for this behavior is presented. The residue D1-E329 interacts with water molecules in the O1 water network that has been suggested recently to supply substrate during the catalytic cycle. Characterization of the D1-E329A mutant with FTIR difference spectroscopy shows that this mutation does not substantially perturb the structure of PSII or the water molecules whose O–H stretching modes change during the catalytic cycle. Furthermore, this result provides additional evidence that the water molecules whose vibrational properties change during the S 1 to S 2 transition are confined approximately to the region bounded by D1-N87, D1-N298, and D2-K317.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A combined theoretical-experimental investigation of thermal transport in low-dose irradiated thorium dioxide

During reactor operation, nuclear fuels are subject to extreme temperature and irradiation conditions which can significantly degrade the fuel's thermal transport properties. The reduction in thermal conductivity of the fuel as a result of irradiation-induced lattice defects is arguably the most important fuel performance metric in regard to reactor efficiency and safety. Because thorium dioxide (ThO2) is suitable as a model system for more complex materials such as UO2 and its mixed oxides, we present a theoretical investigation of thermal conductivity reduction seen in defect-bearing thorium dioxide and compare directly to experimental measurements. Phonon-mediated thermal transport of the fuel is modeled by a solution to the Boltzmann transport equation (BTE) for phonons. A cluster dynamics (CD) model for lattice defect evolution during irradiation predicts defect densities which are used as input to the BTE for modeling phonon-defect scatterings. Phonon scatterings by lattice defects include those from point defects and vacancy clusters and interstitial clusters of various sizes. The CD model is benchmarked against structural defect characterization of irradiated thorium dioxide using electron microscopy. Thermal conductivity predicted by the BTE model is compared to measured values for irradiated thorium dioxide specimens below room temperature to isolate effects of phonon-defect scattering from intrinsic 3-phonon processes, which dominate at higher temperatures. The computed conductivity values are in partial agreement at temperatures close to room temperature while slight deviations are observed at the lowest measured temperatures, suggesting that implemented phonon-defect scattering cross-section expressions may not be adequate for low temperatures. The presented work provides a necessary investigation of the influence of irradiation induced defects on fuel performance and represents a first step toward a full characterization of phonon mediated thermal transport in irradiated materials with complex defect microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Neutral but Impactful: Gallium Cluster-Induced Nanopores from Beam-Blanked Gallium Ion Sources

Neutral atoms originating from liquid metal ion sources are an often-overlooked source of contamination and damage in focused ion beam microscopy. Beyond ions and single atoms, these sources also generate atom clusters. While most studies have investigated charged clusters, here we demonstrate that neutral clusters are also formed. These neutral clusters bypass the electrostatic beam blanking system, allowing them to impinge on samples even when the ion beam is blanked. We investigate this phenomenon using thin (≤20 nm) freestanding membranes of hexagonal boron nitride, silicon, and silicon nitride as targets. Randomly dispersed nanopores that form upon neutral cluster exposure are revealed. The average nanopore diameter is ∼2 nm with a narrow size distribution, suggesting that the atom clusters have a preferred size. Various electron microscopy techniques are used to characterize the nanopores, including high-resolution transmission electron microscopy, multislice ptychography, and electron energy-loss spectroscopy. Finally, we show how electron irradiation in the transmission electron microscope can be used to both remove any amorphous material that may clog the pores and to controllably grow the pores to specific sizes. Tunable nanopores such as these are interesting for nanofluidic applications requiring size-selective membranes.

Byrne, Dana O↗

DOE OSTI2020

Systems biology predicts that fibrosis in tuberculous granulomas may arise through macrophage-to-myofibroblast transformation

Mycobacterium tuberculosis (Mtb) infection causes tuberculosis (TB), a disease characterized by development of granulomas. Granulomas consist of activated immune cells that cluster together to limit bacterial growth and restrict dissemination. Control of the TB epidemic has been limited by lengthy drug regimens, antibiotic resistance, and lack of a robustly efficacious vaccine. Fibrosis commonly occurs during treatment and is associated with both positive and negative disease outcomes in TB but little is known about the processes that initiate fibrosis in granulomas. Human and nonhuman primate granulomas undergoing fibrosis can have spindle-shaped macrophages with fibroblast-like morphologies suggesting a relationship between macrophages, fibroblasts, and granuloma fibrosis. This relationship has been difficult to investigate because of the limited availability of human pathology samples, the time scale involved in human TB, and overlap between fibroblast and myeloid cell markers in tissues. To better understand the origins of fibrosis in TB, we used a computational model of TB granuloma biology to identify factors that drive fibrosis over the course of local disease progression. We validated the model with granulomas from nonhuman primates to delineate myeloid cells and lung-resident fibroblasts. Our results suggest that peripheral granuloma fibrosis, which is commonly observed, can arise through macrophage-to-myofibroblast transformation (MMT). Further, we hypothesize that MMT is induced in M1 macrophages through a sequential combination of inflammatory and anti-inflammatory signaling in granuloma macrophages. We predict that MMT may be a mechanism underlying granuloma-associated fibrosis and warrants further investigation into myeloid cells as drivers of fibrotic disease.

59 BASIC BIOLOGICAL SCIENCES↗